rpas in land survey - eurosdr · rpas in land survey eduserv14 ... rpas project design and flight...

wwweurosdrnet

European Spatial Data Research

RPAS in land survey EduServ14 ndash Spring 2016

Pre-Course Seminar Warsaw

Michael Cramer

Institut fuumlr Photogrammetrie

Universitaumlt Stuttgart

Goumlrres Grenzdoumlrffer

Professur fuumlr Geodaumlsie und

Geoinformatik

Universitaumlt Rostock

wwweurosdrnet


Course Teachers

Michael Cramer

michaelcramerifpuni-stuttgartde


goerresgrenzdoerfferuni-rostockde

wwweurosdrnet


Online Course Phase ndash March 14-25

bull Module 1 ndash Introduction amp Principles of RPAS

bull Module 2 ndash RPAS project design and flight

planning bull Lab 1 ndash Flight planning

bull Lab 2 ndash Camera quality

bull Module 3 ndash RPAS data processing bull Lab 3 ndash Real data processing using Pix4Dmapper

bull Module 4 ndash Legal aspects

wwweurosdrnet


RPAS in land survey Introduction to the course



Geoinformatik


Michael Cramer



wwweurosdrnet


Content ndash Course Introduction

bull RPAS Motivation amp Introduction (10ldquo)

bull Systems amp Sensors (15ldquo)

bull Data Acquisition amp Processing Concepts (20ldquo)

bull Legal Aspects (15ldquo)

wwweurosdrnet


RPAS in land survey Course Introduction ndash Section 1

RPAS Motivation amp Introduction



Geoinformatik


European Spatial Data Research ndash wwweurosdrnet

Potential of RPAS

bull RPAS activities will translate into new jobs

bull US study1 forecasts in the first three years of RPAS integration in the

national airspace more than 70000 jobs will worth more than $136

billion

bull More than 100000 RPAS related Jobs by 2025 in the US

bull For Europe2 about 150000 jobs by 2050 are forecasted

bull Growth potential can only be unleashed if a legal framework is

established at EU level

1 AUVSI (2013) The Economic Impact of Unmanned Aircraft Systems Integration in the US 574p 2 Estimate provided by ASD the AeroSpace and Defence Industries Association of Europe

7

Pa

rt I-1

ndash M

otiva

tio

n amp

In

trod

uctio

n


Motivation

bull Demand of temporally and spatially high resolution aerial

images is growing

bull conventional (manned aircraft) systems are too

expensive and too weather dependent for small areas

(individual objects - some 100 ha)

bull The development of miniaturized autonomous control

systems (GPS INS) for Unmanned Aircraft Vehicles

(UAV) allows systematic aerial surveys rarr interesting

alternative to traditional surveying aircrafts

bull Use of RPAS offers cost savings and greater flexibility

(weather independence)

bull RPAS close the large gap between terrestrial and

airborne or spaceborne spatial data collection 8

Pa

rt I-1

ndash M

otiva

tio

n amp

In

trod

uctio

n


Advantages of Geo data acquisition

with RPAS

9

Scalability Details ndash Overview

Depending on question

Endurance Minutes ndash Days

Depending on the problem

New possibilites Applications impossible or too

expensive in the past

Flexibility Where and when it is

necessary to survey - flight

planning possible on site

RPAS

offer

Ideal for aerial surveys of individual properties and small areas Pa

rt I-1

ndash M

otiva

tio

n amp

In

trod

uctio

n


Use of RPAS in Mapping

Photogrammetry

10 copy Luhmann et al 2006

Pa

rt I ndash

In

trod

uctio

n amp

Motiva

tio

n


RPAS and Photogrammetry

11

bull Current Status

ndash Hottest issue in photogrammetry

ndash Highly automated workflow

ndash Open and public domain products are available (eg Bundler

PMVS MicMac Apero etc)

ndash Commercial products available (Pix4D Agisoft etc)

ndash Ground control points are necessary for high accuracy

ndash Image processing of large blocks requires much time

ndash Excellent results (True) Orthos DOM 3D-point cloud

bull Open Issues

ndash Direct georeferencing

ndash Orthophotos of difficult surfaces

ndash hellip

Pa

rt I ndash

In

trod

uctio

n amp

Motiva

tio

n



Photogrammetry

12

Pa

rt I-1

ndash M

otiva

tio

n amp

In

trod

uctio

n


RPAS (Geo)Applications

13

bull Photography amp Videography ndash for TV cinema press advertising and

corporate publicity

bull Surveying ndash Mapping measuring building inspection crop

monitoring wind turbines inspection Potential for local councils to

use as part of planning applications

bull Emergency Services ndash monitoring spotting hazardous air testing

search and rescue rapid disaster resonance

bull Agriculture ndash Mapping harvest monitoring soil analysis spraying

bull Forestry ndash Inventory and management of pests amp diseases

bull Environmental and ecological change monitoring

bull Entertainment ndash Disney has already filed applications for their use

bull Communications ndash Portable emergency relay stations in remote

locations

bull Short range delivery ()

Pa

rt I-1

ndash M

otiva

tio

n amp

In

trod

uctio

n


RPAS Projects Applications

14

bull Real estate

bull Fire scene inspections

bull Monitoring catastrophes

bull Plane crash scenes

bull Volcanic eruptions

bull Spreading of algae

bull Monitoring aerosol

parameters

bull Forestry management

bull Monitoring of marine

mammals

bull Mapping of sandbank

movements

bull Counting animal populations

bull Forestry monitoring

bull Tree diseases

bull Anti-pirate operations

bull Border controls

bull Road accident analysis

bull Detecting forest firefighting

bull Burial grounds

bull Mapping in coastal areas

bull Geophysical surveys

bull Meteorological research

bull Mapping of sandbanks

bull Identification of plants

bull Perimeter monitoring

bull Power line inspections

bull Railway line inspections

bull Project documentation

bull Supporting forest firefighting

bull Mapping flooding

bull Volcanic eruptions ndash monitoring

amp ash clouds

bull Agriculture ndash harvesting

bull Study of coastal regions

bull Iceberg monitoring

bull Monitoring earthquakes

bull Monitoring amp ship collisions

bull Monitoring nuclear accidents

bull Tool for forest firefighting

bull Mapping of industrial zones

bull Power cable inspections

bull Oil pipeline inspections

bull Police operations


bull Post tsunami mapping

bull Agriculture ndash plant growth

bull Agriculture ndash harvest management

bull Arctic research

bull Environmental surveillance

bull Saltwater infiltration detection

bull Surveillance of volcanoes

bull Forestry ndash monitoring tree growth

bull Historical building inspections

bull Critical infrastructure inspections

bull Gas pipeline inspections

bull Wind turbine inspections

bull Surveillance of coastal regions

bull and much more hellip Pa

rt I-1

ndash M

otiva

tio

n amp

In

trod

uctio

n

wwweurosdrnet



Systems amp Sensors



Geoinformatik


wwweurosdrnet








Terminology

17

bull Aircraft any machine that can derive support in the

atmosphere from the reactions of the air other than the

reaction of the air earthlsquos surface (ICAO Annexes)

bull Autonomous Aircraft an unmanned aircraft that does

not allow pilot intervention in the management of flight

(Amend 43 ICAO Annex 2)

bull Remotely piloted aircraft RPAS ndash an unmanned

aircraft which is piloted from a remote pilot station


bull Unmanned aircraft UA ndash an aircraft which is intended to

operate with no pilot in board note RPA is considered a

subset of UA (ICAO Circular 328)

copy Blyenburgh 2013 ndash RPAS Yearbook


Terminology

18

bull Unmanned aircraft system UAS ndash an unmanned

aircraft system comprises individual system elements

consisting of the UA and any other system element

necessary to enable flight such as remote pilot station

communication link and launch and recovery elements

(CAP722 CAA UK)

bull Unmanned aircraft system UAS ndash An aircraft and its

associated elements which are operated with no pilot on

board (ICAO Circular 328)

Not recommended for further use

bull Unmanned aerial vehicle (UAV) ndash see RPAS

bull Unmanned aerial system (UAS) ndash see RPAS

bull Drone ndash see RPAS copy Blyenburgh 2013 ndash RPAS Yearbook

UA

S S

yste

ms


Components of RPAS

19

RPAS is not a flying object but a complex system of many individual components

Ground station

Avionics

Mission-

planning

Energy

supply

Data transfer

Data transfer

Propulsion and

Energy supply Airframe Mess -

instruments

Offline control

Imaging sensors

Online control Imaging sensors

Control

airframe

Data

- reception - Processing - Distribution

Flight segment

Automated derivation of spatial data for applications

Mis

sio

n C

on

trol

Navigation

- Orientation

- Sensors

Relevance for photogrammetry incl calibration and orientation Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs


RPAS-Classification

20

Category Acronym Range (km)

Flight Altitude (m)

Endurance (h)

MTOW (kg)

Nano η lt 1 100 lt1 lt 0025

Micro micro lt10 250 1 lt5

Mini Mini lt10 150-300 lt2 lt30

Close Range CR 10-30 3000 2-4 150

Short Range SR 30-70 3000 3-6 200

Low Altitude Long Endurance

LALE gt500 3000 gt24 lt30

Medium Altitude Long Endurance

MALE gt500 14000 24-48 1500

High Altitude Long Endurance

HALE gt2000 20000 24-48 4500-12000

Stratospheric STRATO gt2000 20000-30000 gt48 30-

Platform for image-based spatial data

Indoor-platform for image-based spatial data

van Blyenburg 2008

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs


Micro and Mini-RPAS

21

Fixed wing

Multicopter Helicopter

Blimp

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs


Comparison RPAS platforms for

geomatics applications

22

Fixed wing

UAS UAS Model

helicopter Multicopter Ballon Blimp

Technology Handling Simple Complex Simple Simple Naviation ++ ++ ++ - Wind suspectability O - - ++ Robustness ++ + + ++ Noise quiet noisy (fuel) quiet quiet Transport Car trunk Car trunk Car trunk seperate unit Endurance ++ + - ++

Cost Cost + ++ + +

Rolling costs O ++ + +

Mapping Application Speed coverage ++ + + -

Pointing - + ++ ++ Payload O ++ + O Start- u Landing runway everywhere everywhere runway

-- very low - low o medium + high ++ very high

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs


Model planes Challenges Start

23

bull Hand start

ndash Only possible for

RPAS lt 6 kg

ndash Requires experience

bull Start Catapult

ndash heavy

ndash complex

ndash dangerous

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs


Model planes Challenges Landing

24

bull Net

ndash complex not easy to hit

ndash frame can be damaged

bull Parachute

ndash wind dependent

ndash dragged on ground

Pa

rt II

ndash S

yste

ms amp

Se

nso

rs


bdquoStandardldquo Cameras on RPAS

25

Pa

rt II

ndash S

yste

ms amp

Se

nso

rs + small

+ light weight (lt 100g)

+ fixed lens (stable IO)

- Image quality (low light)

- Fish eye lens

+ small


+ external exposure

control

- lens (instable IO)

- Image quality (low

light)

bdquoGoProldquo-Class bdquoConsumer Cameraldquo bdquoDSLRldquo

+ Image quality

+ Image size (gt20 MP)


+ external exposure

control

- heavy (gt 500 g)


Image motion ndash a crucial parameter for

RPAS flights

26

bull In airborne applications image motion u should be below

05 pixel

bull Using a surveying aircraft high airspeeds limit the

minimum GSD or demand for forward motion

compensation (FMC)

bull Multirotor RPAS fly at low speeds exposure times have

to be kept short why

ndash Vibrations of the RPAS

ndash Necessary acceleration and rotation to keep the RPAS stable in

windy conditions

ndash Accelerations and rotations of the stabilization mount incl

latency

119906 =119888 lowast 120596 lowast ∆119905

119862119862119863[micro119898]

Pa

rt II

ndash S

yste

ms amp

Se

nso

rs



RPAS flights

27

Acceptable rotational

speed to keep image

motion below 05 pixel in

relation to the exposure

time

Example

exposure time of 1800 sec

c = 9 mm

allows for rotation speed

of 118degsec

(common max rotation

speed of RPAS during

flights at 2 - 3 Bft)

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs


Stabilized mounts

28

bull State of the art

ndash 2-axis 3-axis stabilized brushless gimbal

ndash Built in independent IMU module

ndash Multiple Control Modes (Photo Video)

ndash Gimbals for GoPro (weight gt 200g)

ndash Gimbals for DSLR (weight gt 1500g)

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs


Current Trends and Innovations

29

bull Multicopter and fixed wing grow together

bull SONGBIRD Aerolution

ndash Combination of multi copter

and fixed wing aircraft

ndash perpendicular starting and

landing

ndash does not require a runway

ndash fastgt 110 km h

ndash Flight time up to 1 h

ndash About 15 kg payload

ndash Powerful autopilot

Quadro copter-Start

Fixed wing flight Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



30

bull RPAS become intelligent and autonomous in which they recognize

their environment

Example eXom ndash Inspection-RPAS from Sensefly for indoor and outdoor

httpswwwsenseflycomdronesexomhtml

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



31

bull RTK-GNSS for navigation and orientation

bull High-precision GNSS allows

ndash More precise Flights

navigation

ndash Accurate image capture


bull Problems

ndash Ambiguities in the vicinity of

buildings

ndash ldquoMetricrdquo camera required

ndash Expensive

ndash hellip

Javad bdquoTriumph F1ldquo

Mavinci bdquoSirius Proldquo

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



32

bull Full exterior orientation information from integrated

GNSSinertial systems for direct georeferencing ie ndash Corridor surveys

ndash reduced image overlaps

Applanix APX15 ndash UAV board

From Applanix product

information httpwwwapplanixcommediadow

nloadsproductsspecsAPX-

1520UAV_Data_Sheetpdf

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



33

bull Cheap RPAS become better and Open Source Projects

bull Example Dji Phantom 3

ndash Flight time ca 20 min

ndash Payload 200 g

ndash Automatic flight

ndash Flight planning software

ndash Cost ca 1200 euro

bull Example ArduPilot

ndash Hard- and Software for Auto

pilot and Gimbal


Dji Phantom 2

ArduPilot Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



34

bull Miniaturized Multi hyperspectral and laser sensors for

RPAS (examples)

bull Rikola Hyperspectral Scanner

ndash Weight ca 600g

ndash Spectral Range 500-900 nm

ndash Frame camera dh simple

Geo referencing

bull Yellow Scan Laserscanner

ndash Weight ca 22 kg

ndash Range ca 100 m

ndash FOV 100deg

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs


RPAS-laser scanning

35

bull RIEGL VUX-1 system

ndash 10 mm survey-grade accuracy

ndash scan speed up to 200 scans second

ndash measurement rate up to 500000

meassec 550 kHz PRR amp 330deg

FOV

ndash operating flight altitude up to more

than 1000 ft

ndash field of view up to 330deg for practically

unrestricted data acquisition

ndash regular point pattern perfectly

parallel scan lines

ndash compact (227x180x125 mm)

lightweight (36 kg) and rugged

See httpwwwrieglcomproductsuasuav-scanningnew-riegl-vux-1

RIEGL RiCOPTER

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs


Tetracam Multispectral cameras

36

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs


Sample Data - Tetracam Multispectral

camera

37

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs


Challenges - Radiometry

38

φi

i

Light

source

Observer

North

φr

r

)(

)()(

ii

rriirrii

E

L

BRDF

L(θiφiθrφr) Reflected radiance

E(θiφi) Irradiance

θiφi Zenith and azimuth angles of incident light

θrφr Zenith and azimuth angles of reflected light

F

D A A

B

C E G

O

Honkavaara 2014

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs

wwweurosdrnet



Michael Cramer



Data Acquisition amp Processing Concepts

wwweurosdrnet








Data Acquisition

RPAS Photogrammetry

=

Terrestrial Photogrammetry

from airborne bdquoTripodsldquo

Land survey Terrestrial Photogrammetry Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts

41


Concept of (stereo) photogrammetry

plsquo(xlsquoylsquo)

plsquolsquo (xlsquolsquoylsquolsquo)

Distance

Photogrammetric stereo reconstruction

Base

xlsquo

xlsquolsquo

Accuracy parameters

bull Imaging geometry

ndash Base

ndash Distance height

bull Measurement

accuracy in image

space

bull Camera geometry

(interior orientation)

bull Exterior orientation

quality

bull Mathematical model

sXY

sZ

42 European Spatial Data Research ndash wwweurosdrnet

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





Distance Z

Base B

xlsquo

xlsquolsquo

sXY

sZ

43

x X y Y

c Z c Z

x X B y Y

c Z c Z

x

c B c BZ

x x p

y yY Z Z

c c

xX Z

c


Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





Distance Z

Base B

xlsquo

xlsquolsquo

stereo normal case used

for accuracy estimation

Z b x

Y X b x

Zm

B

m

s s

s s s

sXY

sZ

2

Z Z

x Z b Z

Z B

Zm

c

s s

s s s

Accuracy

44


Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


Concept of (multiple stereo)

photogrammetry




xlsquo

xlsquolsquo

plsquolsquolsquo (xlsquolsquolsquoylsquolsquolsquo)

plsquolsquolsquolsquo (xlsquolsquolsquolsquoylsquolsquolsquolsquo)

xlsquolsquolsquo xlsquolsquolsquolsquo

sXY

sZ

The stereo model was

the traditional working unit in

(analog) airborne

photogrammetry with digital

imaging this changed to the

multiple stereo model ray

processing This also is the

case in terrestrial and RPAS

projects

45

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


Photogrammetric blocks

Factors influencing accuracy

bull Accuracy of image measurements

bull Image scale

bull Configuration (base-to-heightdistance ratio)

bull Design factor for close-range blocks

XYZ b xq ms s

Z b x

Y X b x

Zm

m

Bs s

s s s

Airborne blocks Close-range blocks

46

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


Aerial Triangulation

Collinearity equation

Transformation Image Object

Transformation Object Image

11 21 31

13 23 33

12 22 32

13 23 33

r X r Y r Zx z

r X r Y r Z

r X r Y r Zy z

r X r Y r Z

0

0

0

X X X

Y Y Y

Z Z Z

0

0

0

x x x

y y y

z z z c

with 11 12 13

31 32 33

r x r y r zX Z

r x r y r z

21 22 23

31 32 33

r x r y r cY Z

r x r y r c

Note model assumes cartesian

coordinate frames

stringent approach pre-

transformation of object

coordinates

alternative correction of earth

curvature at object or image

coordinates (note no error in

image space in its closer sense)

47

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts

European Spatial Data Research ndash wwweurosdrnet 48

Extended collinearity equations

0

0

0

X X X

Y Y Y

Z Z Z

0

0

0

x x x

y y y

z z z c

Transformation from Object Image

11 21 31

13 23 33

12 22 32

13 23 33

r X r Y r Zx z x

r X r Y r Z

r X r Y r Zy z y

r X r Y r Z

typically the standard model is amended by additional parameters (AP) x y

allow for compensation of systematic errors in image space and estimation

camera calibration parameters (dependent on block geometry)

models are functions of reduced image coordinates

classification of AP sets

physical models obtained from physical interpretable params (D Brown)

pure mathematical models without physical meanings

combinedmixed models (combination of former two)

with

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


Camera Calibration

bull Most often camera calibration is done in a so-called self-

calibration approach (camera calibrated in the block itself)

bull For a priori calibration (to get approx values) a mobile test field

(possibly with coded targets) might be used

49

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


Extended collinearity equations Indirect georeferencing

Object coordinate

system

camera

P object point

Plsquo image point

O perspective centre

cx

cz

cy

0X

X

)( Rp

p

standard geometry used in

indirect georeferencing

X

Y

Z

0

l l l Cam

Cam X X R p

50

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


Extended collinearity equations GNSSinertial EO parameters

Inertial Measurement

Unit cx

cz

cy

X

Y

Z

bzby

bx

GNSS antenna phase centre

0X

X

)( Rp

p

0

bX

GPS

bX

Cam

bX

e

Modified geometry used in

direct georeferencing

Object coordinate

system

camera

P object point

Plsquo image point


51

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



bull Coordinate transformation Image Object ndash frame sensor

ndash Note for rolling shutter cameras the change of EO parameters during exposure might be modelled

Keep in mind

ndash Navigation angles from GPSinertial are non identical with the typically used photogrammetric angles

ndash GPSinertial data have to be related to the imaging sensor to be oriented so-called boresight alignment corrections

bull Translation offsets

bull Misalignment matrix

0 l l Cab b b

Ca

m

b Pm Cam GPSR X XX X R x

b b

Cam GPS X X

( )b

Cam R

( ) ( )l n

b b R R

52

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


Photogrammetric block layouts

(classical) airborne

close-range

53

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Standard-AT

GNSS supported AT

few control points

Calibrated cams +

self-calibration

(math models)

GNSSinertial data

bdquolevelledldquo camera

AAT (tie points from

FBMLSM)

RPAS

Few control points

Full in-situ camera

calibration

(physical models

GNSS (code)

Attitudes gt 0hellip20deg

Structure from Motion

(SIFT key points)

camera calibration

Initial Orientation Set-

up of Image Block

Orientation of image

block

Product generation

DTMDSM (Dense

Matching) amp Ortho

Transformation into

object coordinate frame

Process chain

54

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


CV ndash Multiple View Geometry

Structure from Motion SfM

bull Scene geometry (structure) Given 2D point

matches in two or more images where are the

corresponding points in 3D

bull Correspondence (stereo matching) Given a

point in just one image how does it constrain the

position of the corresponding point in another

image

bull Camera geometry (motion) Given a set of

corresponding points in two or more images

what are the camera matrices for these views

55

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




56

bull Given m images of n fixed 3D points

xij = Pi Xj i = 1 hellip m j = 1 hellip n

bull Problem estimate m projection matrices Pi and

n 3D points Xj from the mn correspondences xij

x1j

x2j

x3j

Xj

P1

P2

P3

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




Feature detection using SIFT ASIFT SURF

copy R Fergus 2014 57

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




copy R Fergus 2014

Incremental SfM

58

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




Matching features in stereo-pairs


Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Algorithm

bull Initialize 3D model by selecting suitable

stereo pair from all available images

bull Expand 3D model ndash If there are connected images add that image which

contains the largest number of existing 3D points

ndash Compute orientation of corresponding camera station

(DLT)

ndash Spatial intersection of additional stereo points

ndash Compute bundle block adjustment (global best estimate)

60

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


ca

me

ras

points

61


Algorithm

bull Initialize motion from two

images using fundamental

matrix and SIFT matching ndash Initialize structure

bull For each additional view ndash Determine projection matrix of new

camera using all the known 3D points

that are visible in its image ndash

calibration

ndash Refine and extend structure compute

new 3D points

re-optimize existing points that are

also seen by this camera ndash

triangulation

bull Refine structure and motion

bundle adjustment

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


ca

me

ras

points

62


Algorithm







calibration


new 3D points



triangulation


bundle adjustment

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Algorithm

Example VisualSfM httpccwumevsfm Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


Image Matching

bull Basic assumption Corresponding points in images usually

have similar gray values

bull Problems from matching ambiguity due to

ndash Similar grey values depict different points ie surface patches

ndash Homogenous texture

bull Identical points appear different

ndash Changes in illumination different look angle noise

bull Strategies to overcome ambiguities

ndash Use of robust similarity measures

bull Match windows instead of single pixels

ndash Constrain correspondence with additional information

bull Epipolar geometry to restrict matching to 1D problem

64

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


Dense Image Matching

Semi global matching

bull Match single pixels with global algorithms such that a global

energy function is minimized

bull Additional assumptions constraints to overcome ambiguity

bull Semi-global matching

ndash Matching dense intensity-based

ndash Global optimization approach using a global model

ndash Semi approximation fast numerical solution

65

Intensity image Disparity image using a

correlation matching method

Disparity image using

Semi Global Matching

Hirschmuumlller (2005)

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


EduServ 12 (2014)

SfM amp Dense image matching

66

Course High density image matching

Prof Dr Norbert Haala

University of Stuttgart Germany

see httpwwweurosdrneteducationpast

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts

wwweurosdrnet



Legal Aspects



Geoinformatik


wwweurosdrnet








RPAS and legal issues

69

bull Scenario 1 A farmer with a 2000 ha farm throws a RPAS into the air

in the morning and a little later he gets fully automatically up to date

information about all of its fields

bull Scenario 2 After an emergency call the fire fighters starts an RPAS

flying a few miles ahead and once the arrive at the fire valuable

information is already available at the scene

bull Scenario 3 After an emergency call the police launches an RPAS

and scans generously the whole scenery to acquire all possible data

for subsequent use

Are these scenarios possible or legal today

bull No because of legal restrictions and privacy issues Pa

rt I-4

ndash L

ega

l Asp

ects


Where can I fly at all

Structure of the lower airspace

70

bull RPAS lt25 kg may operate only in uncontrolled airspace

(G) lt 1000 ft (2500 ft) above ground

bull Flights in airspace D and F requires a special permission

from air traffic control (ATC) Pa

rt I-4

ndash L

ega

l Asp

ects


Airspace Usage - Airspace Maps

httpmapsopenaipnet 71


Privacy

bull No seperate RPAS-privacy laws Normal laws

apply

bull It is forbidden to take images AND distribute

them IF people can be identified WITHOUT

permission UNLESS there is a justified reason

72

Pa

rt I-4

ndash L

ega

l Asp

ects


What is the state of play in Europe

bull 14 countries have regulation (not harmonised)

bull 5 countries are developing rules

bull 6 allow operations under strict conditions

bull 2800+ civil approved commercial companies and

growing

bull Most operators and manufacturers have no

aviation background

bull Economic potential estimated at several billions

before end 2020

bull Pragmatic European approach hellip

73

Pa

rt I-4

ndash L

ega

l Asp

ects


Legal framework - current status

Germany

bull RPAS gt 25 kg and flights beyond line of sight (BLOS)

are generally prohibited exceptions are possible

(Repressive prohibition)

bull Distinction between permit free and subject to

authorization flights is the purpose of the flight

ndash Sports and Leisure = RC ie permit free

ndash Commercial or science etc = RPAS ie subject to authorization

(Permit required)

bull Permits issued by state authorities

bull Permits require proof of insurance no pilot licence no

certification of UAS no ID-plate

74

Pa

rt I-4

ndash L

ega

l Asp

ects


75



77

httprpas-regulationscom


European Regulation

78

bull European Aviation Satefy Agency (EASA) is responsible

for civilian RPAS gt 150 kg

bull 6 March 215 ndash Riga Declaration

bull By 2016 EASA plans to finalize a corresponding

framework

bull In addition to the mandatory task the EU wants to

harmonize national regulations for all RPAS lt150 kg

bull EASA Regulation will come in 2017ndash2018 (after approval

of basic regulation (EASA-VO (EG) Nr 2162008)

+++ 18122015 Technical Opinion - A-NPA 2015-10 +++

Pa

rt I-4

ndash L

ega

l Asp

ects


EU vision of the integration of UAS in

the civilian airspace

79

Pa

rt I-4

ndash L

ega

l Asp

ects


EASA Technical Opinion ndash

3 Categories

80

Open Category

ndash Equal rules for

model planes

and UAS

ndash Geofencing

ndash Subcategories

in relation to

potential harm

ndash Exemption for

toys

ndash Control thru

police

Certified Category

bull Specific for large

UAS gt 25 kg

bull Certification

similar to

manned aviation

bull Pilot licence

(PPL)

bull Certification of

Flight Operation

through Certified

Entities

Specific Category

bull Mostly for

commercial

UAS-users

bull bdquosmallldquo licence

bull Requirements

depend on use

of operation


Flight Operation)

through bdquoCertified

Entitiesldquo

Pa

rt I-4

ndash L

ega

l Asp

ects


EASA Technical Opinion - Geofencing

81

Pa

rt I-4

ndash L

ega

l Asp

ects


Conclusions for civil commercial

RPAS segments

82

bull RPAS with lt 5 - 30 kg (no integration in general

aviation (max 150 m altitude and easy flights within

visual line of sight (VLOS))

bull Small RPAS - good value for money and well suited

to carry a (photogrammetric) camera

bull Potential for commercially successful applications

Max take off weight differs from country to country Pa

rt I-4

ndash L

ega

l Asp

ects



RPAS segments

bull RPAS with gt 30 kg (primarily military use possible

future integration into general airspace)

bull Requirements for payload telemetry TCAS security

systems (redundancy) lead to large and therefore

expensive systems thus commercial civil usage

appears very difficult

bull Regulation issues for beyond line of sight (BLOS)-

flights will remain critical for the upcoming 5 ndash 15

years

bull EU has decided on a common list of minimums in

order to enable cross border work in the future

83

Pa

rt I-4

ndash L

ega

l Asp

ects

wwweurosdrnet


Course Teachers

Michael Cramer

michaelcramerifpuni-stuttgartde


goerresgrenzdoerfferuni-rostockde

wwweurosdrnet









wwweurosdrnet





Geoinformatik


Michael Cramer



wwweurosdrnet







wwweurosdrnet






Geoinformatik



Potential of RPAS




billion






7

Pa

rt I-1

ndash M

otiva

tio

n amp

In

trod

uctio

n


Motivation


images is growing












Pa

rt I-1

ndash M

otiva

tio

n amp

In

trod

uctio

n



with RPAS

9










RPAS

offer


rt I-1

ndash M

otiva

tio

n amp

In

trod

uctio

n



Photogrammetry


Pa

rt I ndash

In

trod

uctio

n amp

Motiva

tio

n



11

bull Current Status









bull Open Issues



ndash hellip

Pa

rt I ndash

In

trod

uctio

n amp

Motiva

tio

n



Photogrammetry

12

Pa

rt I-1

ndash M

otiva

tio

n amp

In

trod

uctio

n



13


corporate publicity











locations


Pa

rt I-1

ndash M

otiva

tio

n amp

In

trod

uctio

n



14

bull Real estate







parameters



mammals


movements



bull Tree diseases





bull Burial grounds













amp ash clouds



























rt I-1

ndash M

otiva

tio

n amp

In

trod

uctio

n

wwweurosdrnet



Systems amp Sensors



Geoinformatik


wwweurosdrnet








Terminology

17















Terminology

18






(CAP722 CAA UK)








UA

S S

yste

ms


Components of RPAS

19


Ground station

Avionics

Mission-

planning

Energy

supply

Data transfer

Data transfer

Propulsion and


instruments

Offline control

Imaging sensors


Control

airframe

Data


Flight segment


Mis

sio

n C

on

trol

Navigation

- Orientation

- Sensors


rt I-2

ndash S

yste

ms amp

Se

nso

rs


RPAS-Classification

20


Flight Altitude (m)

Endurance (h)

MTOW (kg)




Close Range CR 10-30 3000 2-4 150

Short Range SR 30-70 3000 3-6 200




MALE gt500 14000 24-48 1500


HALE gt2000 20000 24-48 4500-12000




van Blyenburg 2008

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs


Micro and Mini-RPAS

21

Fixed wing


Blimp

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs




22

Fixed wing

UAS UAS Model



Cost Cost + ++ + +





Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



23

bull Hand start


RPAS lt 6 kg


bull Start Catapult

ndash heavy

ndash complex

ndash dangerous

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



24

bull Net



bull Parachute



Pa

rt II

ndash S

yste

ms amp

Se

nso

rs



25

Pa

rt II

ndash S

yste

ms amp

Se

nso

rs + small




- Fish eye lens

+ small


+ external exposure

control



light)


+ Image quality



+ external exposure

control

- heavy (gt 500 g)



RPAS flights

26


05 pixel



compensation (FMC)





windy conditions


latency

119906 =119888 lowast 120596 lowast ∆119905

119862119862119863[micro119898]

Pa

rt II

ndash S

yste

ms amp

Se

nso

rs



RPAS flights

27


speed to keep image



time

Example


c = 9 mm


of 118degsec




Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs


Stabilized mounts

28







Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



29






landing






Quadro copter-Start


rt I-2

ndash S

yste

ms amp

Se

nso

rs



30


their environment



Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



31




navigation



bull Problems


buildings


ndash Expensive

ndash hellip



Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



32









Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



33




ndash Payload 200 g






pilot and Gimbal


Dji Phantom 2

ArduPilot Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



34


RPAS (examples)





Geo referencing




ndash FOV 100deg

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs


RPAS-laser scanning

35






FOV


than 1000 ft




parallel scan lines




RIEGL RiCOPTER

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



36

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



camera

37

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



38

φi

i

Light

source

Observer

North

φr

r

)(

)()(

ii

rriirrii

E

L

BRDF





F

D A A

B

C E G

O

Honkavaara 2014

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs

wwweurosdrnet



Michael Cramer




wwweurosdrnet








Data Acquisition

RPAS Photogrammetry

=




rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts

41





Distance


Base

xlsquo

xlsquolsquo

Accuracy parameters


ndash Base


bull Measurement

accuracy in image

space




quality


sXY

sZ


Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





Distance Z

Base B

xlsquo

xlsquolsquo

sXY

sZ

43

x X y Y

c Z c Z

x X B y Y

c Z c Z

x

c B c BZ

x x p

y yY Z Z

c c

xX Z

c


Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





Distance Z

Base B

xlsquo

xlsquolsquo



Z b x

Y X b x

Zm

B

m

s s

s s s

sXY

sZ

2

Z Z

x Z b Z

Z B

Zm

c

s s

s s s

Accuracy

44


Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



photogrammetry




xlsquo

xlsquolsquo




sXY

sZ



(analog) airborne






projects

45

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





bull Image scale



XYZ b xq ms s

Z b x

Y X b x

Zm

m

Bs s

s s s


46

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts






11 21 31

13 23 33

12 22 32

13 23 33

r X r Y r Zx z

r X r Y r Z

r X r Y r Zy z

r X r Y r Z

0

0

0

X X X

Y Y Y

Z Z Z

0

0

0

x x x

y y y

z z z c

with 11 12 13

31 32 33

r x r y r zX Z

r x r y r z

21 22 23

31 32 33

r x r y r cY Z

r x r y r c


coordinate frames



coordinates





47

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



0

0

0

X X X

Y Y Y

Z Z Z

0

0

0

x x x

y y y

z z z c


11 21 31

13 23 33

12 22 32

13 23 33

r X r Y r Zx z x

r X r Y r Z

r X r Y r Zy z y

r X r Y r Z









with

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


Camera Calibration





49

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Object coordinate

system

camera

P object point

Plsquo image point


cx

cz

cy

0X

X

)( Rp

p



X

Y

Z

0

l l l Cam

Cam X X R p

50

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




Unit cx

cz

cy

X

Y

Z

bzby

bx


0X

X

)( Rp

p

0

bX

GPS

bX

Cam

bX

e



Object coordinate

system

camera

P object point

Plsquo image point


51

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





Keep in mind





0 l l Cab b b

Ca

m


b b

Cam GPS X X

( )b

Cam R

( ) ( )l n

b b R R

52

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




close-range

53

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Standard-AT

GNSS supported AT

few control points

Calibrated cams +

self-calibration

(math models)

GNSSinertial data



FBMLSM)

RPAS

Few control points

Full in-situ camera

calibration

(physical models

GNSS (code)



(SIFT key points)

camera calibration


up of Image Block


block

Product generation

DTMDSM (Dense

Matching) amp Ortho

Transformation into


Process chain

54

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts










image




55

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




56





x1j

x2j

x3j

Xj

P1

P2

P3

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




copy R Fergus 2014

Incremental SfM

58

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Algorithm






(DLT)



60

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


ca

me

ras

points

61


Algorithm







calibration


new 3D points



triangulation


bundle adjustment

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


ca

me

ras

points

62


Algorithm







calibration


new 3D points



triangulation


bundle adjustment

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Algorithm


rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


Image Matching













64

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts











65






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


EduServ 12 (2014)


66





Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts

wwweurosdrnet



Legal Aspects



Geoinformatik


wwweurosdrnet









69









for subsequent use



rt I-4

ndash L

ega

l Asp

ects




70





rt I-4

ndash L

ega

l Asp

ects





Privacy


apply




72

Pa

rt I-4

ndash L

ega

l Asp

ects







growing


aviation background


before end 2020


73

Pa

rt I-4

ndash L

ega

l Asp

ects



Germany








(Permit required)




74

Pa

rt I-4

ndash L

ega

l Asp

ects


75



77



European Regulation

78





framework






Pa

rt I-4

ndash L

ega

l Asp

ects




79

Pa

rt I-4

ndash L

ega

l Asp

ects



3 Categories

80

Open Category


model planes

and UAS

ndash Geofencing

ndash Subcategories

in relation to

potential harm

ndash Exemption for

toys

ndash Control thru

police

Certified Category


UAS gt 25 kg

bull Certification

similar to

manned aviation

bull Pilot licence

(PPL)


Flight Operation

through Certified

Entities

Specific Category

bull Mostly for

commercial

UAS-users


bull Requirements

depend on use

of operation


Flight Operation)


Entitiesldquo

Pa

rt I-4

ndash L

ega

l Asp

ects



81

Pa

rt I-4

ndash L

ega

l Asp

ects



RPAS segments

82








rt I-4

ndash L

ega

l Asp

ects



RPAS segments









years



83

Pa

rt I-4

ndash L

ega

l Asp

ects

wwweurosdrnet









wwweurosdrnet





Geoinformatik


Michael Cramer



wwweurosdrnet







wwweurosdrnet






Geoinformatik



Potential of RPAS




billion






7

Pa

rt I-1

ndash M

otiva

tio

n amp

In

trod

uctio

n


Motivation


images is growing












Pa

rt I-1

ndash M

otiva

tio

n amp

In

trod

uctio

n



with RPAS

9










RPAS

offer


rt I-1

ndash M

otiva

tio

n amp

In

trod

uctio

n



Photogrammetry


Pa

rt I ndash

In

trod

uctio

n amp

Motiva

tio

n



11

bull Current Status









bull Open Issues



ndash hellip

Pa

rt I ndash

In

trod

uctio

n amp

Motiva

tio

n



Photogrammetry

12

Pa

rt I-1

ndash M

otiva

tio

n amp

In

trod

uctio

n



13


corporate publicity











locations


Pa

rt I-1

ndash M

otiva

tio

n amp

In

trod

uctio

n



14

bull Real estate







parameters



mammals


movements



bull Tree diseases





bull Burial grounds













amp ash clouds



























rt I-1

ndash M

otiva

tio

n amp

In

trod

uctio

n

wwweurosdrnet



Systems amp Sensors



Geoinformatik


wwweurosdrnet








Terminology

17















Terminology

18






(CAP722 CAA UK)








UA

S S

yste

ms


Components of RPAS

19


Ground station

Avionics

Mission-

planning

Energy

supply

Data transfer

Data transfer

Propulsion and


instruments

Offline control

Imaging sensors


Control

airframe

Data


Flight segment


Mis

sio

n C

on

trol

Navigation

- Orientation

- Sensors


rt I-2

ndash S

yste

ms amp

Se

nso

rs


RPAS-Classification

20


Flight Altitude (m)

Endurance (h)

MTOW (kg)




Close Range CR 10-30 3000 2-4 150

Short Range SR 30-70 3000 3-6 200




MALE gt500 14000 24-48 1500


HALE gt2000 20000 24-48 4500-12000




van Blyenburg 2008

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs


Micro and Mini-RPAS

21

Fixed wing


Blimp

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs




22

Fixed wing

UAS UAS Model



Cost Cost + ++ + +





Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



23

bull Hand start


RPAS lt 6 kg


bull Start Catapult

ndash heavy

ndash complex

ndash dangerous

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



24

bull Net



bull Parachute



Pa

rt II

ndash S

yste

ms amp

Se

nso

rs



25

Pa

rt II

ndash S

yste

ms amp

Se

nso

rs + small




- Fish eye lens

+ small


+ external exposure

control



light)


+ Image quality



+ external exposure

control

- heavy (gt 500 g)



RPAS flights

26


05 pixel



compensation (FMC)





windy conditions


latency

119906 =119888 lowast 120596 lowast ∆119905

119862119862119863[micro119898]

Pa

rt II

ndash S

yste

ms amp

Se

nso

rs



RPAS flights

27


speed to keep image



time

Example


c = 9 mm


of 118degsec




Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs


Stabilized mounts

28







Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



29






landing






Quadro copter-Start


rt I-2

ndash S

yste

ms amp

Se

nso

rs



30


their environment



Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



31




navigation



bull Problems


buildings


ndash Expensive

ndash hellip



Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



32









Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



33




ndash Payload 200 g






pilot and Gimbal


Dji Phantom 2

ArduPilot Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



34


RPAS (examples)





Geo referencing




ndash FOV 100deg

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs


RPAS-laser scanning

35






FOV


than 1000 ft




parallel scan lines




RIEGL RiCOPTER

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



36

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



camera

37

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



38

φi

i

Light

source

Observer

North

φr

r

)(

)()(

ii

rriirrii

E

L

BRDF





F

D A A

B

C E G

O

Honkavaara 2014

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs

wwweurosdrnet



Michael Cramer




wwweurosdrnet








Data Acquisition

RPAS Photogrammetry

=




rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts

41





Distance


Base

xlsquo

xlsquolsquo

Accuracy parameters


ndash Base


bull Measurement

accuracy in image

space




quality


sXY

sZ


Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





Distance Z

Base B

xlsquo

xlsquolsquo

sXY

sZ

43

x X y Y

c Z c Z

x X B y Y

c Z c Z

x

c B c BZ

x x p

y yY Z Z

c c

xX Z

c


Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





Distance Z

Base B

xlsquo

xlsquolsquo



Z b x

Y X b x

Zm

B

m

s s

s s s

sXY

sZ

2

Z Z

x Z b Z

Z B

Zm

c

s s

s s s

Accuracy

44


Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



photogrammetry




xlsquo

xlsquolsquo




sXY

sZ



(analog) airborne






projects

45

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





bull Image scale



XYZ b xq ms s

Z b x

Y X b x

Zm

m

Bs s

s s s


46

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts






11 21 31

13 23 33

12 22 32

13 23 33

r X r Y r Zx z

r X r Y r Z

r X r Y r Zy z

r X r Y r Z

0

0

0

X X X

Y Y Y

Z Z Z

0

0

0

x x x

y y y

z z z c

with 11 12 13

31 32 33

r x r y r zX Z

r x r y r z

21 22 23

31 32 33

r x r y r cY Z

r x r y r c


coordinate frames



coordinates





47

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



0

0

0

X X X

Y Y Y

Z Z Z

0

0

0

x x x

y y y

z z z c


11 21 31

13 23 33

12 22 32

13 23 33

r X r Y r Zx z x

r X r Y r Z

r X r Y r Zy z y

r X r Y r Z









with

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


Camera Calibration





49

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Object coordinate

system

camera

P object point

Plsquo image point


cx

cz

cy

0X

X

)( Rp

p



X

Y

Z

0

l l l Cam

Cam X X R p

50

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




Unit cx

cz

cy

X

Y

Z

bzby

bx


0X

X

)( Rp

p

0

bX

GPS

bX

Cam

bX

e



Object coordinate

system

camera

P object point

Plsquo image point


51

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





Keep in mind





0 l l Cab b b

Ca

m


b b

Cam GPS X X

( )b

Cam R

( ) ( )l n

b b R R

52

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




close-range

53

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Standard-AT

GNSS supported AT

few control points

Calibrated cams +

self-calibration

(math models)

GNSSinertial data



FBMLSM)

RPAS

Few control points

Full in-situ camera

calibration

(physical models

GNSS (code)



(SIFT key points)

camera calibration


up of Image Block


block

Product generation

DTMDSM (Dense

Matching) amp Ortho

Transformation into


Process chain

54

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts










image




55

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




56





x1j

x2j

x3j

Xj

P1

P2

P3

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




copy R Fergus 2014

Incremental SfM

58

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Algorithm






(DLT)



60

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


ca

me

ras

points

61


Algorithm







calibration


new 3D points



triangulation


bundle adjustment

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


ca

me

ras

points

62


Algorithm







calibration


new 3D points



triangulation


bundle adjustment

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Algorithm


rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


Image Matching













64

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts











65






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


EduServ 12 (2014)


66





Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts

wwweurosdrnet



Legal Aspects



Geoinformatik


wwweurosdrnet









69









for subsequent use



rt I-4

ndash L

ega

l Asp

ects




70





rt I-4

ndash L

ega

l Asp

ects





Privacy


apply




72

Pa

rt I-4

ndash L

ega

l Asp

ects







growing


aviation background


before end 2020


73

Pa

rt I-4

ndash L

ega

l Asp

ects



Germany








(Permit required)




74

Pa

rt I-4

ndash L

ega

l Asp

ects


75



77



European Regulation

78





framework






Pa

rt I-4

ndash L

ega

l Asp

ects




79

Pa

rt I-4

ndash L

ega

l Asp

ects



3 Categories

80

Open Category


model planes

and UAS

ndash Geofencing

ndash Subcategories

in relation to

potential harm

ndash Exemption for

toys

ndash Control thru

police

Certified Category


UAS gt 25 kg

bull Certification

similar to

manned aviation

bull Pilot licence

(PPL)


Flight Operation

through Certified

Entities

Specific Category

bull Mostly for

commercial

UAS-users


bull Requirements

depend on use

of operation


Flight Operation)


Entitiesldquo

Pa

rt I-4

ndash L

ega

l Asp

ects



81

Pa

rt I-4

ndash L

ega

l Asp

ects



RPAS segments

82








rt I-4

ndash L

ega

l Asp

ects



RPAS segments









years



83

Pa

rt I-4

ndash L

ega

l Asp

ects

wwweurosdrnet





Geoinformatik


Michael Cramer



wwweurosdrnet







wwweurosdrnet






Geoinformatik



Potential of RPAS




billion






7

Pa

rt I-1

ndash M

otiva

tio

n amp

In

trod

uctio

n


Motivation


images is growing












Pa

rt I-1

ndash M

otiva

tio

n amp

In

trod

uctio

n



with RPAS

9










RPAS

offer


rt I-1

ndash M

otiva

tio

n amp

In

trod

uctio

n



Photogrammetry


Pa

rt I ndash

In

trod

uctio

n amp

Motiva

tio

n



11

bull Current Status









bull Open Issues



ndash hellip

Pa

rt I ndash

In

trod

uctio

n amp

Motiva

tio

n



Photogrammetry

12

Pa

rt I-1

ndash M

otiva

tio

n amp

In

trod

uctio

n



13


corporate publicity











locations


Pa

rt I-1

ndash M

otiva

tio

n amp

In

trod

uctio

n



14

bull Real estate







parameters



mammals


movements



bull Tree diseases





bull Burial grounds













amp ash clouds



























rt I-1

ndash M

otiva

tio

n amp

In

trod

uctio

n

wwweurosdrnet



Systems amp Sensors



Geoinformatik


wwweurosdrnet








Terminology

17















Terminology

18






(CAP722 CAA UK)








UA

S S

yste

ms


Components of RPAS

19


Ground station

Avionics

Mission-

planning

Energy

supply

Data transfer

Data transfer

Propulsion and


instruments

Offline control

Imaging sensors


Control

airframe

Data


Flight segment


Mis

sio

n C

on

trol

Navigation

- Orientation

- Sensors


rt I-2

ndash S

yste

ms amp

Se

nso

rs


RPAS-Classification

20


Flight Altitude (m)

Endurance (h)

MTOW (kg)




Close Range CR 10-30 3000 2-4 150

Short Range SR 30-70 3000 3-6 200




MALE gt500 14000 24-48 1500


HALE gt2000 20000 24-48 4500-12000




van Blyenburg 2008

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs


Micro and Mini-RPAS

21

Fixed wing


Blimp

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs




22

Fixed wing

UAS UAS Model



Cost Cost + ++ + +





Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



23

bull Hand start


RPAS lt 6 kg


bull Start Catapult

ndash heavy

ndash complex

ndash dangerous

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



24

bull Net



bull Parachute



Pa

rt II

ndash S

yste

ms amp

Se

nso

rs



25

Pa

rt II

ndash S

yste

ms amp

Se

nso

rs + small




- Fish eye lens

+ small


+ external exposure

control



light)


+ Image quality



+ external exposure

control

- heavy (gt 500 g)



RPAS flights

26


05 pixel



compensation (FMC)





windy conditions


latency

119906 =119888 lowast 120596 lowast ∆119905

119862119862119863[micro119898]

Pa

rt II

ndash S

yste

ms amp

Se

nso

rs



RPAS flights

27


speed to keep image



time

Example


c = 9 mm


of 118degsec




Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs


Stabilized mounts

28







Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



29






landing






Quadro copter-Start


rt I-2

ndash S

yste

ms amp

Se

nso

rs



30


their environment



Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



31




navigation



bull Problems


buildings


ndash Expensive

ndash hellip



Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



32









Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



33




ndash Payload 200 g






pilot and Gimbal


Dji Phantom 2

ArduPilot Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



34


RPAS (examples)





Geo referencing




ndash FOV 100deg

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs


RPAS-laser scanning

35






FOV


than 1000 ft




parallel scan lines




RIEGL RiCOPTER

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



36

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



camera

37

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



38

φi

i

Light

source

Observer

North

φr

r

)(

)()(

ii

rriirrii

E

L

BRDF





F

D A A

B

C E G

O

Honkavaara 2014

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs

wwweurosdrnet



Michael Cramer




wwweurosdrnet








Data Acquisition

RPAS Photogrammetry

=




rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts

41





Distance


Base

xlsquo

xlsquolsquo

Accuracy parameters


ndash Base


bull Measurement

accuracy in image

space




quality


sXY

sZ


Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





Distance Z

Base B

xlsquo

xlsquolsquo

sXY

sZ

43

x X y Y

c Z c Z

x X B y Y

c Z c Z

x

c B c BZ

x x p

y yY Z Z

c c

xX Z

c


Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





Distance Z

Base B

xlsquo

xlsquolsquo



Z b x

Y X b x

Zm

B

m

s s

s s s

sXY

sZ

2

Z Z

x Z b Z

Z B

Zm

c

s s

s s s

Accuracy

44


Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



photogrammetry




xlsquo

xlsquolsquo




sXY

sZ



(analog) airborne






projects

45

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





bull Image scale



XYZ b xq ms s

Z b x

Y X b x

Zm

m

Bs s

s s s


46

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts






11 21 31

13 23 33

12 22 32

13 23 33

r X r Y r Zx z

r X r Y r Z

r X r Y r Zy z

r X r Y r Z

0

0

0

X X X

Y Y Y

Z Z Z

0

0

0

x x x

y y y

z z z c

with 11 12 13

31 32 33

r x r y r zX Z

r x r y r z

21 22 23

31 32 33

r x r y r cY Z

r x r y r c


coordinate frames



coordinates





47

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



0

0

0

X X X

Y Y Y

Z Z Z

0

0

0

x x x

y y y

z z z c


11 21 31

13 23 33

12 22 32

13 23 33

r X r Y r Zx z x

r X r Y r Z

r X r Y r Zy z y

r X r Y r Z









with

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


Camera Calibration





49

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Object coordinate

system

camera

P object point

Plsquo image point


cx

cz

cy

0X

X

)( Rp

p



X

Y

Z

0

l l l Cam

Cam X X R p

50

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




Unit cx

cz

cy

X

Y

Z

bzby

bx


0X

X

)( Rp

p

0

bX

GPS

bX

Cam

bX

e



Object coordinate

system

camera

P object point

Plsquo image point


51

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





Keep in mind





0 l l Cab b b

Ca

m


b b

Cam GPS X X

( )b

Cam R

( ) ( )l n

b b R R

52

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




close-range

53

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Standard-AT

GNSS supported AT

few control points

Calibrated cams +

self-calibration

(math models)

GNSSinertial data



FBMLSM)

RPAS

Few control points

Full in-situ camera

calibration

(physical models

GNSS (code)



(SIFT key points)

camera calibration


up of Image Block


block

Product generation

DTMDSM (Dense

Matching) amp Ortho

Transformation into


Process chain

54

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts










image




55

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




56





x1j

x2j

x3j

Xj

P1

P2

P3

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




copy R Fergus 2014

Incremental SfM

58

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Algorithm






(DLT)



60

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


ca

me

ras

points

61


Algorithm







calibration


new 3D points



triangulation


bundle adjustment

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


ca

me

ras

points

62


Algorithm







calibration


new 3D points



triangulation


bundle adjustment

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Algorithm


rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


Image Matching













64

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts











65






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


EduServ 12 (2014)


66





Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts

wwweurosdrnet



Legal Aspects



Geoinformatik


wwweurosdrnet









69









for subsequent use



rt I-4

ndash L

ega

l Asp

ects




70





rt I-4

ndash L

ega

l Asp

ects





Privacy


apply




72

Pa

rt I-4

ndash L

ega

l Asp

ects







growing


aviation background


before end 2020


73

Pa

rt I-4

ndash L

ega

l Asp

ects



Germany








(Permit required)




74

Pa

rt I-4

ndash L

ega

l Asp

ects


75



77



European Regulation

78





framework






Pa

rt I-4

ndash L

ega

l Asp

ects




79

Pa

rt I-4

ndash L

ega

l Asp

ects



3 Categories

80

Open Category


model planes

and UAS

ndash Geofencing

ndash Subcategories

in relation to

potential harm

ndash Exemption for

toys

ndash Control thru

police

Certified Category


UAS gt 25 kg

bull Certification

similar to

manned aviation

bull Pilot licence

(PPL)


Flight Operation

through Certified

Entities

Specific Category

bull Mostly for

commercial

UAS-users


bull Requirements

depend on use

of operation


Flight Operation)


Entitiesldquo

Pa

rt I-4

ndash L

ega

l Asp

ects



81

Pa

rt I-4

ndash L

ega

l Asp

ects



RPAS segments

82








rt I-4

ndash L

ega

l Asp

ects



RPAS segments









years



83

Pa

rt I-4

ndash L

ega

l Asp

ects

wwweurosdrnet







wwweurosdrnet






Geoinformatik



Potential of RPAS




billion






7

Pa

rt I-1

ndash M

otiva

tio

n amp

In

trod

uctio

n


Motivation


images is growing












Pa

rt I-1

ndash M

otiva

tio

n amp

In

trod

uctio

n



with RPAS

9










RPAS

offer


rt I-1

ndash M

otiva

tio

n amp

In

trod

uctio

n



Photogrammetry


Pa

rt I ndash

In

trod

uctio

n amp

Motiva

tio

n



11

bull Current Status









bull Open Issues



ndash hellip

Pa

rt I ndash

In

trod

uctio

n amp

Motiva

tio

n



Photogrammetry

12

Pa

rt I-1

ndash M

otiva

tio

n amp

In

trod

uctio

n



13


corporate publicity











locations


Pa

rt I-1

ndash M

otiva

tio

n amp

In

trod

uctio

n



14

bull Real estate







parameters



mammals


movements



bull Tree diseases





bull Burial grounds













amp ash clouds



























rt I-1

ndash M

otiva

tio

n amp

In

trod

uctio

n

wwweurosdrnet



Systems amp Sensors



Geoinformatik


wwweurosdrnet








Terminology

17















Terminology

18






(CAP722 CAA UK)








UA

S S

yste

ms


Components of RPAS

19


Ground station

Avionics

Mission-

planning

Energy

supply

Data transfer

Data transfer

Propulsion and


instruments

Offline control

Imaging sensors


Control

airframe

Data


Flight segment


Mis

sio

n C

on

trol

Navigation

- Orientation

- Sensors


rt I-2

ndash S

yste

ms amp

Se

nso

rs


RPAS-Classification

20


Flight Altitude (m)

Endurance (h)

MTOW (kg)




Close Range CR 10-30 3000 2-4 150

Short Range SR 30-70 3000 3-6 200




MALE gt500 14000 24-48 1500


HALE gt2000 20000 24-48 4500-12000




van Blyenburg 2008

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs


Micro and Mini-RPAS

21

Fixed wing


Blimp

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs




22

Fixed wing

UAS UAS Model



Cost Cost + ++ + +





Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



23

bull Hand start


RPAS lt 6 kg


bull Start Catapult

ndash heavy

ndash complex

ndash dangerous

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



24

bull Net



bull Parachute



Pa

rt II

ndash S

yste

ms amp

Se

nso

rs



25

Pa

rt II

ndash S

yste

ms amp

Se

nso

rs + small




- Fish eye lens

+ small


+ external exposure

control



light)


+ Image quality



+ external exposure

control

- heavy (gt 500 g)



RPAS flights

26


05 pixel



compensation (FMC)





windy conditions


latency

119906 =119888 lowast 120596 lowast ∆119905

119862119862119863[micro119898]

Pa

rt II

ndash S

yste

ms amp

Se

nso

rs



RPAS flights

27


speed to keep image



time

Example


c = 9 mm


of 118degsec




Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs


Stabilized mounts

28







Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



29






landing






Quadro copter-Start


rt I-2

ndash S

yste

ms amp

Se

nso

rs



30


their environment



Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



31




navigation



bull Problems


buildings


ndash Expensive

ndash hellip



Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



32









Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



33




ndash Payload 200 g






pilot and Gimbal


Dji Phantom 2

ArduPilot Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



34


RPAS (examples)





Geo referencing




ndash FOV 100deg

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs


RPAS-laser scanning

35






FOV


than 1000 ft




parallel scan lines




RIEGL RiCOPTER

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



36

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



camera

37

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



38

φi

i

Light

source

Observer

North

φr

r

)(

)()(

ii

rriirrii

E

L

BRDF





F

D A A

B

C E G

O

Honkavaara 2014

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs

wwweurosdrnet



Michael Cramer




wwweurosdrnet








Data Acquisition

RPAS Photogrammetry

=




rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts

41





Distance


Base

xlsquo

xlsquolsquo

Accuracy parameters


ndash Base


bull Measurement

accuracy in image

space




quality


sXY

sZ


Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





Distance Z

Base B

xlsquo

xlsquolsquo

sXY

sZ

43

x X y Y

c Z c Z

x X B y Y

c Z c Z

x

c B c BZ

x x p

y yY Z Z

c c

xX Z

c


Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





Distance Z

Base B

xlsquo

xlsquolsquo



Z b x

Y X b x

Zm

B

m

s s

s s s

sXY

sZ

2

Z Z

x Z b Z

Z B

Zm

c

s s

s s s

Accuracy

44


Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



photogrammetry




xlsquo

xlsquolsquo




sXY

sZ



(analog) airborne






projects

45

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





bull Image scale



XYZ b xq ms s

Z b x

Y X b x

Zm

m

Bs s

s s s


46

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts






11 21 31

13 23 33

12 22 32

13 23 33

r X r Y r Zx z

r X r Y r Z

r X r Y r Zy z

r X r Y r Z

0

0

0

X X X

Y Y Y

Z Z Z

0

0

0

x x x

y y y

z z z c

with 11 12 13

31 32 33

r x r y r zX Z

r x r y r z

21 22 23

31 32 33

r x r y r cY Z

r x r y r c


coordinate frames



coordinates





47

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



0

0

0

X X X

Y Y Y

Z Z Z

0

0

0

x x x

y y y

z z z c


11 21 31

13 23 33

12 22 32

13 23 33

r X r Y r Zx z x

r X r Y r Z

r X r Y r Zy z y

r X r Y r Z









with

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


Camera Calibration





49

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Object coordinate

system

camera

P object point

Plsquo image point


cx

cz

cy

0X

X

)( Rp

p



X

Y

Z

0

l l l Cam

Cam X X R p

50

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




Unit cx

cz

cy

X

Y

Z

bzby

bx


0X

X

)( Rp

p

0

bX

GPS

bX

Cam

bX

e



Object coordinate

system

camera

P object point

Plsquo image point


51

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





Keep in mind





0 l l Cab b b

Ca

m


b b

Cam GPS X X

( )b

Cam R

( ) ( )l n

b b R R

52

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




close-range

53

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Standard-AT

GNSS supported AT

few control points

Calibrated cams +

self-calibration

(math models)

GNSSinertial data



FBMLSM)

RPAS

Few control points

Full in-situ camera

calibration

(physical models

GNSS (code)



(SIFT key points)

camera calibration


up of Image Block


block

Product generation

DTMDSM (Dense

Matching) amp Ortho

Transformation into


Process chain

54

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts










image




55

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




56





x1j

x2j

x3j

Xj

P1

P2

P3

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




copy R Fergus 2014

Incremental SfM

58

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Algorithm






(DLT)



60

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


ca

me

ras

points

61


Algorithm







calibration


new 3D points



triangulation


bundle adjustment

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


ca

me

ras

points

62


Algorithm







calibration


new 3D points



triangulation


bundle adjustment

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Algorithm


rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


Image Matching













64

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts











65






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


EduServ 12 (2014)


66





Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts

wwweurosdrnet



Legal Aspects



Geoinformatik


wwweurosdrnet









69









for subsequent use



rt I-4

ndash L

ega

l Asp

ects




70





rt I-4

ndash L

ega

l Asp

ects





Privacy


apply




72

Pa

rt I-4

ndash L

ega

l Asp

ects







growing


aviation background


before end 2020


73

Pa

rt I-4

ndash L

ega

l Asp

ects



Germany








(Permit required)




74

Pa

rt I-4

ndash L

ega

l Asp

ects


75



77



European Regulation

78





framework






Pa

rt I-4

ndash L

ega

l Asp

ects




79

Pa

rt I-4

ndash L

ega

l Asp

ects



3 Categories

80

Open Category


model planes

and UAS

ndash Geofencing

ndash Subcategories

in relation to

potential harm

ndash Exemption for

toys

ndash Control thru

police

Certified Category


UAS gt 25 kg

bull Certification

similar to

manned aviation

bull Pilot licence

(PPL)


Flight Operation

through Certified

Entities

Specific Category

bull Mostly for

commercial

UAS-users


bull Requirements

depend on use

of operation


Flight Operation)


Entitiesldquo

Pa

rt I-4

ndash L

ega

l Asp

ects



81

Pa

rt I-4

ndash L

ega

l Asp

ects



RPAS segments

82








rt I-4

ndash L

ega

l Asp

ects



RPAS segments









years



83

Pa

rt I-4

ndash L

ega

l Asp

ects

wwweurosdrnet






Geoinformatik



Potential of RPAS




billion






7

Pa

rt I-1

ndash M

otiva

tio

n amp

In

trod

uctio

n


Motivation


images is growing












Pa

rt I-1

ndash M

otiva

tio

n amp

In

trod

uctio

n



with RPAS

9










RPAS

offer


rt I-1

ndash M

otiva

tio

n amp

In

trod

uctio

n



Photogrammetry


Pa

rt I ndash

In

trod

uctio

n amp

Motiva

tio

n



11

bull Current Status









bull Open Issues



ndash hellip

Pa

rt I ndash

In

trod

uctio

n amp

Motiva

tio

n



Photogrammetry

12

Pa

rt I-1

ndash M

otiva

tio

n amp

In

trod

uctio

n



13


corporate publicity











locations


Pa

rt I-1

ndash M

otiva

tio

n amp

In

trod

uctio

n



14

bull Real estate







parameters



mammals


movements



bull Tree diseases





bull Burial grounds













amp ash clouds



























rt I-1

ndash M

otiva

tio

n amp

In

trod

uctio

n

wwweurosdrnet



Systems amp Sensors



Geoinformatik


wwweurosdrnet








Terminology

17















Terminology

18






(CAP722 CAA UK)








UA

S S

yste

ms


Components of RPAS

19


Ground station

Avionics

Mission-

planning

Energy

supply

Data transfer

Data transfer

Propulsion and


instruments

Offline control

Imaging sensors


Control

airframe

Data


Flight segment


Mis

sio

n C

on

trol

Navigation

- Orientation

- Sensors


rt I-2

ndash S

yste

ms amp

Se

nso

rs


RPAS-Classification

20


Flight Altitude (m)

Endurance (h)

MTOW (kg)




Close Range CR 10-30 3000 2-4 150

Short Range SR 30-70 3000 3-6 200




MALE gt500 14000 24-48 1500


HALE gt2000 20000 24-48 4500-12000




van Blyenburg 2008

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs


Micro and Mini-RPAS

21

Fixed wing


Blimp

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs




22

Fixed wing

UAS UAS Model



Cost Cost + ++ + +





Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



23

bull Hand start


RPAS lt 6 kg


bull Start Catapult

ndash heavy

ndash complex

ndash dangerous

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



24

bull Net



bull Parachute



Pa

rt II

ndash S

yste

ms amp

Se

nso

rs



25

Pa

rt II

ndash S

yste

ms amp

Se

nso

rs + small




- Fish eye lens

+ small


+ external exposure

control



light)


+ Image quality



+ external exposure

control

- heavy (gt 500 g)



RPAS flights

26


05 pixel



compensation (FMC)





windy conditions


latency

119906 =119888 lowast 120596 lowast ∆119905

119862119862119863[micro119898]

Pa

rt II

ndash S

yste

ms amp

Se

nso

rs



RPAS flights

27


speed to keep image



time

Example


c = 9 mm


of 118degsec




Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs


Stabilized mounts

28







Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



29






landing






Quadro copter-Start


rt I-2

ndash S

yste

ms amp

Se

nso

rs



30


their environment



Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



31




navigation



bull Problems


buildings


ndash Expensive

ndash hellip



Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



32









Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



33




ndash Payload 200 g






pilot and Gimbal


Dji Phantom 2

ArduPilot Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



34


RPAS (examples)





Geo referencing




ndash FOV 100deg

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs


RPAS-laser scanning

35






FOV


than 1000 ft




parallel scan lines




RIEGL RiCOPTER

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



36

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



camera

37

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



38

φi

i

Light

source

Observer

North

φr

r

)(

)()(

ii

rriirrii

E

L

BRDF





F

D A A

B

C E G

O

Honkavaara 2014

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs

wwweurosdrnet



Michael Cramer




wwweurosdrnet








Data Acquisition

RPAS Photogrammetry

=




rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts

41





Distance


Base

xlsquo

xlsquolsquo

Accuracy parameters


ndash Base


bull Measurement

accuracy in image

space




quality


sXY

sZ


Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





Distance Z

Base B

xlsquo

xlsquolsquo

sXY

sZ

43

x X y Y

c Z c Z

x X B y Y

c Z c Z

x

c B c BZ

x x p

y yY Z Z

c c

xX Z

c


Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





Distance Z

Base B

xlsquo

xlsquolsquo



Z b x

Y X b x

Zm

B

m

s s

s s s

sXY

sZ

2

Z Z

x Z b Z

Z B

Zm

c

s s

s s s

Accuracy

44


Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



photogrammetry




xlsquo

xlsquolsquo




sXY

sZ



(analog) airborne






projects

45

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





bull Image scale



XYZ b xq ms s

Z b x

Y X b x

Zm

m

Bs s

s s s


46

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts






11 21 31

13 23 33

12 22 32

13 23 33

r X r Y r Zx z

r X r Y r Z

r X r Y r Zy z

r X r Y r Z

0

0

0

X X X

Y Y Y

Z Z Z

0

0

0

x x x

y y y

z z z c

with 11 12 13

31 32 33

r x r y r zX Z

r x r y r z

21 22 23

31 32 33

r x r y r cY Z

r x r y r c


coordinate frames



coordinates





47

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



0

0

0

X X X

Y Y Y

Z Z Z

0

0

0

x x x

y y y

z z z c


11 21 31

13 23 33

12 22 32

13 23 33

r X r Y r Zx z x

r X r Y r Z

r X r Y r Zy z y

r X r Y r Z









with

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


Camera Calibration





49

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Object coordinate

system

camera

P object point

Plsquo image point


cx

cz

cy

0X

X

)( Rp

p



X

Y

Z

0

l l l Cam

Cam X X R p

50

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




Unit cx

cz

cy

X

Y

Z

bzby

bx


0X

X

)( Rp

p

0

bX

GPS

bX

Cam

bX

e



Object coordinate

system

camera

P object point

Plsquo image point


51

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





Keep in mind





0 l l Cab b b

Ca

m


b b

Cam GPS X X

( )b

Cam R

( ) ( )l n

b b R R

52

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




close-range

53

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Standard-AT

GNSS supported AT

few control points

Calibrated cams +

self-calibration

(math models)

GNSSinertial data



FBMLSM)

RPAS

Few control points

Full in-situ camera

calibration

(physical models

GNSS (code)



(SIFT key points)

camera calibration


up of Image Block


block

Product generation

DTMDSM (Dense

Matching) amp Ortho

Transformation into


Process chain

54

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts










image




55

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




56





x1j

x2j

x3j

Xj

P1

P2

P3

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




copy R Fergus 2014

Incremental SfM

58

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Algorithm






(DLT)



60

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


ca

me

ras

points

61


Algorithm







calibration


new 3D points



triangulation


bundle adjustment

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


ca

me

ras

points

62


Algorithm







calibration


new 3D points



triangulation


bundle adjustment

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Algorithm


rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


Image Matching













64

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts











65






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


EduServ 12 (2014)


66





Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts

wwweurosdrnet



Legal Aspects



Geoinformatik


wwweurosdrnet









69









for subsequent use



rt I-4

ndash L

ega

l Asp

ects




70





rt I-4

ndash L

ega

l Asp

ects





Privacy


apply




72

Pa

rt I-4

ndash L

ega

l Asp

ects







growing


aviation background


before end 2020


73

Pa

rt I-4

ndash L

ega

l Asp

ects



Germany








(Permit required)




74

Pa

rt I-4

ndash L

ega

l Asp

ects


75



77



European Regulation

78





framework






Pa

rt I-4

ndash L

ega

l Asp

ects




79

Pa

rt I-4

ndash L

ega

l Asp

ects



3 Categories

80

Open Category


model planes

and UAS

ndash Geofencing

ndash Subcategories

in relation to

potential harm

ndash Exemption for

toys

ndash Control thru

police

Certified Category


UAS gt 25 kg

bull Certification

similar to

manned aviation

bull Pilot licence

(PPL)


Flight Operation

through Certified

Entities

Specific Category

bull Mostly for

commercial

UAS-users


bull Requirements

depend on use

of operation


Flight Operation)


Entitiesldquo

Pa

rt I-4

ndash L

ega

l Asp

ects



81

Pa

rt I-4

ndash L

ega

l Asp

ects



RPAS segments

82








rt I-4

ndash L

ega

l Asp

ects



RPAS segments









years



83

Pa

rt I-4

ndash L

ega

l Asp

ects


Potential of RPAS




billion






7

Pa

rt I-1

ndash M

otiva

tio

n amp

In

trod

uctio

n


Motivation


images is growing












Pa

rt I-1

ndash M

otiva

tio

n amp

In

trod

uctio

n



with RPAS

9










RPAS

offer


rt I-1

ndash M

otiva

tio

n amp

In

trod

uctio

n



Photogrammetry


Pa

rt I ndash

In

trod

uctio

n amp

Motiva

tio

n



11

bull Current Status









bull Open Issues



ndash hellip

Pa

rt I ndash

In

trod

uctio

n amp

Motiva

tio

n



Photogrammetry

12

Pa

rt I-1

ndash M

otiva

tio

n amp

In

trod

uctio

n



13


corporate publicity











locations


Pa

rt I-1

ndash M

otiva

tio

n amp

In

trod

uctio

n



14

bull Real estate







parameters



mammals


movements



bull Tree diseases





bull Burial grounds













amp ash clouds



























rt I-1

ndash M

otiva

tio

n amp

In

trod

uctio

n

wwweurosdrnet



Systems amp Sensors



Geoinformatik


wwweurosdrnet








Terminology

17















Terminology

18






(CAP722 CAA UK)








UA

S S

yste

ms


Components of RPAS

19


Ground station

Avionics

Mission-

planning

Energy

supply

Data transfer

Data transfer

Propulsion and


instruments

Offline control

Imaging sensors


Control

airframe

Data


Flight segment


Mis

sio

n C

on

trol

Navigation

- Orientation

- Sensors


rt I-2

ndash S

yste

ms amp

Se

nso

rs


RPAS-Classification

20


Flight Altitude (m)

Endurance (h)

MTOW (kg)




Close Range CR 10-30 3000 2-4 150

Short Range SR 30-70 3000 3-6 200




MALE gt500 14000 24-48 1500


HALE gt2000 20000 24-48 4500-12000




van Blyenburg 2008

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs


Micro and Mini-RPAS

21

Fixed wing


Blimp

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs




22

Fixed wing

UAS UAS Model



Cost Cost + ++ + +





Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



23

bull Hand start


RPAS lt 6 kg


bull Start Catapult

ndash heavy

ndash complex

ndash dangerous

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



24

bull Net



bull Parachute



Pa

rt II

ndash S

yste

ms amp

Se

nso

rs



25

Pa

rt II

ndash S

yste

ms amp

Se

nso

rs + small




- Fish eye lens

+ small


+ external exposure

control



light)


+ Image quality



+ external exposure

control

- heavy (gt 500 g)



RPAS flights

26


05 pixel



compensation (FMC)





windy conditions


latency

119906 =119888 lowast 120596 lowast ∆119905

119862119862119863[micro119898]

Pa

rt II

ndash S

yste

ms amp

Se

nso

rs



RPAS flights

27


speed to keep image



time

Example


c = 9 mm


of 118degsec




Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs


Stabilized mounts

28







Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



29






landing






Quadro copter-Start


rt I-2

ndash S

yste

ms amp

Se

nso

rs



30


their environment



Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



31




navigation



bull Problems


buildings


ndash Expensive

ndash hellip



Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



32









Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



33




ndash Payload 200 g






pilot and Gimbal


Dji Phantom 2

ArduPilot Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



34


RPAS (examples)





Geo referencing




ndash FOV 100deg

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs


RPAS-laser scanning

35






FOV


than 1000 ft




parallel scan lines




RIEGL RiCOPTER

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



36

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



camera

37

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



38

φi

i

Light

source

Observer

North

φr

r

)(

)()(

ii

rriirrii

E

L

BRDF





F

D A A

B

C E G

O

Honkavaara 2014

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs

wwweurosdrnet



Michael Cramer




wwweurosdrnet








Data Acquisition

RPAS Photogrammetry

=




rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts

41





Distance


Base

xlsquo

xlsquolsquo

Accuracy parameters


ndash Base


bull Measurement

accuracy in image

space




quality


sXY

sZ


Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





Distance Z

Base B

xlsquo

xlsquolsquo

sXY

sZ

43

x X y Y

c Z c Z

x X B y Y

c Z c Z

x

c B c BZ

x x p

y yY Z Z

c c

xX Z

c


Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





Distance Z

Base B

xlsquo

xlsquolsquo



Z b x

Y X b x

Zm

B

m

s s

s s s

sXY

sZ

2

Z Z

x Z b Z

Z B

Zm

c

s s

s s s

Accuracy

44


Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



photogrammetry




xlsquo

xlsquolsquo




sXY

sZ



(analog) airborne






projects

45

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





bull Image scale



XYZ b xq ms s

Z b x

Y X b x

Zm

m

Bs s

s s s


46

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts






11 21 31

13 23 33

12 22 32

13 23 33

r X r Y r Zx z

r X r Y r Z

r X r Y r Zy z

r X r Y r Z

0

0

0

X X X

Y Y Y

Z Z Z

0

0

0

x x x

y y y

z z z c

with 11 12 13

31 32 33

r x r y r zX Z

r x r y r z

21 22 23

31 32 33

r x r y r cY Z

r x r y r c


coordinate frames



coordinates





47

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



0

0

0

X X X

Y Y Y

Z Z Z

0

0

0

x x x

y y y

z z z c


11 21 31

13 23 33

12 22 32

13 23 33

r X r Y r Zx z x

r X r Y r Z

r X r Y r Zy z y

r X r Y r Z









with

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


Camera Calibration





49

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Object coordinate

system

camera

P object point

Plsquo image point


cx

cz

cy

0X

X

)( Rp

p



X

Y

Z

0

l l l Cam

Cam X X R p

50

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




Unit cx

cz

cy

X

Y

Z

bzby

bx


0X

X

)( Rp

p

0

bX

GPS

bX

Cam

bX

e



Object coordinate

system

camera

P object point

Plsquo image point


51

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





Keep in mind





0 l l Cab b b

Ca

m


b b

Cam GPS X X

( )b

Cam R

( ) ( )l n

b b R R

52

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




close-range

53

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Standard-AT

GNSS supported AT

few control points

Calibrated cams +

self-calibration

(math models)

GNSSinertial data



FBMLSM)

RPAS

Few control points

Full in-situ camera

calibration

(physical models

GNSS (code)



(SIFT key points)

camera calibration


up of Image Block


block

Product generation

DTMDSM (Dense

Matching) amp Ortho

Transformation into


Process chain

54

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts










image




55

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




56





x1j

x2j

x3j

Xj

P1

P2

P3

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




copy R Fergus 2014

Incremental SfM

58

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Algorithm






(DLT)



60

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


ca

me

ras

points

61


Algorithm







calibration


new 3D points



triangulation


bundle adjustment

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


ca

me

ras

points

62


Algorithm







calibration


new 3D points



triangulation


bundle adjustment

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Algorithm


rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


Image Matching













64

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts











65






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


EduServ 12 (2014)


66





Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts

wwweurosdrnet



Legal Aspects



Geoinformatik


wwweurosdrnet









69









for subsequent use



rt I-4

ndash L

ega

l Asp

ects




70





rt I-4

ndash L

ega

l Asp

ects





Privacy


apply




72

Pa

rt I-4

ndash L

ega

l Asp

ects







growing


aviation background


before end 2020


73

Pa

rt I-4

ndash L

ega

l Asp

ects



Germany








(Permit required)




74

Pa

rt I-4

ndash L

ega

l Asp

ects


75



77



European Regulation

78





framework






Pa

rt I-4

ndash L

ega

l Asp

ects




79

Pa

rt I-4

ndash L

ega

l Asp

ects



3 Categories

80

Open Category


model planes

and UAS

ndash Geofencing

ndash Subcategories

in relation to

potential harm

ndash Exemption for

toys

ndash Control thru

police

Certified Category


UAS gt 25 kg

bull Certification

similar to

manned aviation

bull Pilot licence

(PPL)


Flight Operation

through Certified

Entities

Specific Category

bull Mostly for

commercial

UAS-users


bull Requirements

depend on use

of operation


Flight Operation)


Entitiesldquo

Pa

rt I-4

ndash L

ega

l Asp

ects



81

Pa

rt I-4

ndash L

ega

l Asp

ects



RPAS segments

82








rt I-4

ndash L

ega

l Asp

ects



RPAS segments









years



83

Pa

rt I-4

ndash L

ega

l Asp

ects


Motivation


images is growing












Pa

rt I-1

ndash M

otiva

tio

n amp

In

trod

uctio

n



with RPAS

9










RPAS

offer


rt I-1

ndash M

otiva

tio

n amp

In

trod

uctio

n



Photogrammetry


Pa

rt I ndash

In

trod

uctio

n amp

Motiva

tio

n



11

bull Current Status









bull Open Issues



ndash hellip

Pa

rt I ndash

In

trod

uctio

n amp

Motiva

tio

n



Photogrammetry

12

Pa

rt I-1

ndash M

otiva

tio

n amp

In

trod

uctio

n



13


corporate publicity











locations


Pa

rt I-1

ndash M

otiva

tio

n amp

In

trod

uctio

n



14

bull Real estate







parameters



mammals


movements



bull Tree diseases





bull Burial grounds













amp ash clouds



























rt I-1

ndash M

otiva

tio

n amp

In

trod

uctio

n

wwweurosdrnet



Systems amp Sensors



Geoinformatik


wwweurosdrnet








Terminology

17















Terminology

18






(CAP722 CAA UK)








UA

S S

yste

ms


Components of RPAS

19


Ground station

Avionics

Mission-

planning

Energy

supply

Data transfer

Data transfer

Propulsion and


instruments

Offline control

Imaging sensors


Control

airframe

Data


Flight segment


Mis

sio

n C

on

trol

Navigation

- Orientation

- Sensors


rt I-2

ndash S

yste

ms amp

Se

nso

rs


RPAS-Classification

20


Flight Altitude (m)

Endurance (h)

MTOW (kg)




Close Range CR 10-30 3000 2-4 150

Short Range SR 30-70 3000 3-6 200




MALE gt500 14000 24-48 1500


HALE gt2000 20000 24-48 4500-12000




van Blyenburg 2008

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs


Micro and Mini-RPAS

21

Fixed wing


Blimp

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs




22

Fixed wing

UAS UAS Model



Cost Cost + ++ + +





Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



23

bull Hand start


RPAS lt 6 kg


bull Start Catapult

ndash heavy

ndash complex

ndash dangerous

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



24

bull Net



bull Parachute



Pa

rt II

ndash S

yste

ms amp

Se

nso

rs



25

Pa

rt II

ndash S

yste

ms amp

Se

nso

rs + small




- Fish eye lens

+ small


+ external exposure

control



light)


+ Image quality



+ external exposure

control

- heavy (gt 500 g)



RPAS flights

26


05 pixel



compensation (FMC)





windy conditions


latency

119906 =119888 lowast 120596 lowast ∆119905

119862119862119863[micro119898]

Pa

rt II

ndash S

yste

ms amp

Se

nso

rs



RPAS flights

27


speed to keep image



time

Example


c = 9 mm


of 118degsec




Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs


Stabilized mounts

28







Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



29






landing






Quadro copter-Start


rt I-2

ndash S

yste

ms amp

Se

nso

rs



30


their environment



Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



31




navigation



bull Problems


buildings


ndash Expensive

ndash hellip



Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



32









Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



33




ndash Payload 200 g






pilot and Gimbal


Dji Phantom 2

ArduPilot Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



34


RPAS (examples)





Geo referencing




ndash FOV 100deg

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs


RPAS-laser scanning

35






FOV


than 1000 ft




parallel scan lines




RIEGL RiCOPTER

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



36

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



camera

37

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



38

φi

i

Light

source

Observer

North

φr

r

)(

)()(

ii

rriirrii

E

L

BRDF





F

D A A

B

C E G

O

Honkavaara 2014

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs

wwweurosdrnet



Michael Cramer




wwweurosdrnet








Data Acquisition

RPAS Photogrammetry

=




rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts

41





Distance


Base

xlsquo

xlsquolsquo

Accuracy parameters


ndash Base


bull Measurement

accuracy in image

space




quality


sXY

sZ


Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





Distance Z

Base B

xlsquo

xlsquolsquo

sXY

sZ

43

x X y Y

c Z c Z

x X B y Y

c Z c Z

x

c B c BZ

x x p

y yY Z Z

c c

xX Z

c


Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





Distance Z

Base B

xlsquo

xlsquolsquo



Z b x

Y X b x

Zm

B

m

s s

s s s

sXY

sZ

2

Z Z

x Z b Z

Z B

Zm

c

s s

s s s

Accuracy

44


Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



photogrammetry




xlsquo

xlsquolsquo




sXY

sZ



(analog) airborne






projects

45

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





bull Image scale



XYZ b xq ms s

Z b x

Y X b x

Zm

m

Bs s

s s s


46

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts






11 21 31

13 23 33

12 22 32

13 23 33

r X r Y r Zx z

r X r Y r Z

r X r Y r Zy z

r X r Y r Z

0

0

0

X X X

Y Y Y

Z Z Z

0

0

0

x x x

y y y

z z z c

with 11 12 13

31 32 33

r x r y r zX Z

r x r y r z

21 22 23

31 32 33

r x r y r cY Z

r x r y r c


coordinate frames



coordinates





47

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



0

0

0

X X X

Y Y Y

Z Z Z

0

0

0

x x x

y y y

z z z c


11 21 31

13 23 33

12 22 32

13 23 33

r X r Y r Zx z x

r X r Y r Z

r X r Y r Zy z y

r X r Y r Z









with

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


Camera Calibration





49

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Object coordinate

system

camera

P object point

Plsquo image point


cx

cz

cy

0X

X

)( Rp

p



X

Y

Z

0

l l l Cam

Cam X X R p

50

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




Unit cx

cz

cy

X

Y

Z

bzby

bx


0X

X

)( Rp

p

0

bX

GPS

bX

Cam

bX

e



Object coordinate

system

camera

P object point

Plsquo image point


51

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





Keep in mind





0 l l Cab b b

Ca

m


b b

Cam GPS X X

( )b

Cam R

( ) ( )l n

b b R R

52

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




close-range

53

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Standard-AT

GNSS supported AT

few control points

Calibrated cams +

self-calibration

(math models)

GNSSinertial data



FBMLSM)

RPAS

Few control points

Full in-situ camera

calibration

(physical models

GNSS (code)



(SIFT key points)

camera calibration


up of Image Block


block

Product generation

DTMDSM (Dense

Matching) amp Ortho

Transformation into


Process chain

54

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts










image




55

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




56





x1j

x2j

x3j

Xj

P1

P2

P3

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




copy R Fergus 2014

Incremental SfM

58

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Algorithm






(DLT)



60

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


ca

me

ras

points

61


Algorithm







calibration


new 3D points



triangulation


bundle adjustment

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


ca

me

ras

points

62


Algorithm







calibration


new 3D points



triangulation


bundle adjustment

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Algorithm


rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


Image Matching













64

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts











65






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


EduServ 12 (2014)


66





Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts

wwweurosdrnet



Legal Aspects



Geoinformatik


wwweurosdrnet









69









for subsequent use



rt I-4

ndash L

ega

l Asp

ects




70





rt I-4

ndash L

ega

l Asp

ects





Privacy


apply




72

Pa

rt I-4

ndash L

ega

l Asp

ects







growing


aviation background


before end 2020


73

Pa

rt I-4

ndash L

ega

l Asp

ects



Germany








(Permit required)




74

Pa

rt I-4

ndash L

ega

l Asp

ects


75



77



European Regulation

78





framework






Pa

rt I-4

ndash L

ega

l Asp

ects




79

Pa

rt I-4

ndash L

ega

l Asp

ects



3 Categories

80

Open Category


model planes

and UAS

ndash Geofencing

ndash Subcategories

in relation to

potential harm

ndash Exemption for

toys

ndash Control thru

police

Certified Category


UAS gt 25 kg

bull Certification

similar to

manned aviation

bull Pilot licence

(PPL)


Flight Operation

through Certified

Entities

Specific Category

bull Mostly for

commercial

UAS-users


bull Requirements

depend on use

of operation


Flight Operation)


Entitiesldquo

Pa

rt I-4

ndash L

ega

l Asp

ects



81

Pa

rt I-4

ndash L

ega

l Asp

ects



RPAS segments

82








rt I-4

ndash L

ega

l Asp

ects



RPAS segments









years



83

Pa

rt I-4

ndash L

ega

l Asp

ects



with RPAS

9










RPAS

offer


rt I-1

ndash M

otiva

tio

n amp

In

trod

uctio

n



Photogrammetry


Pa

rt I ndash

In

trod

uctio

n amp

Motiva

tio

n



11

bull Current Status









bull Open Issues



ndash hellip

Pa

rt I ndash

In

trod

uctio

n amp

Motiva

tio

n



Photogrammetry

12

Pa

rt I-1

ndash M

otiva

tio

n amp

In

trod

uctio

n



13


corporate publicity











locations


Pa

rt I-1

ndash M

otiva

tio

n amp

In

trod

uctio

n



14

bull Real estate







parameters



mammals


movements



bull Tree diseases





bull Burial grounds













amp ash clouds



























rt I-1

ndash M

otiva

tio

n amp

In

trod

uctio

n

wwweurosdrnet



Systems amp Sensors



Geoinformatik


wwweurosdrnet








Terminology

17















Terminology

18






(CAP722 CAA UK)








UA

S S

yste

ms


Components of RPAS

19


Ground station

Avionics

Mission-

planning

Energy

supply

Data transfer

Data transfer

Propulsion and


instruments

Offline control

Imaging sensors


Control

airframe

Data


Flight segment


Mis

sio

n C

on

trol

Navigation

- Orientation

- Sensors


rt I-2

ndash S

yste

ms amp

Se

nso

rs


RPAS-Classification

20


Flight Altitude (m)

Endurance (h)

MTOW (kg)




Close Range CR 10-30 3000 2-4 150

Short Range SR 30-70 3000 3-6 200




MALE gt500 14000 24-48 1500


HALE gt2000 20000 24-48 4500-12000




van Blyenburg 2008

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs


Micro and Mini-RPAS

21

Fixed wing


Blimp

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs




22

Fixed wing

UAS UAS Model



Cost Cost + ++ + +





Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



23

bull Hand start


RPAS lt 6 kg


bull Start Catapult

ndash heavy

ndash complex

ndash dangerous

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



24

bull Net



bull Parachute



Pa

rt II

ndash S

yste

ms amp

Se

nso

rs



25

Pa

rt II

ndash S

yste

ms amp

Se

nso

rs + small




- Fish eye lens

+ small


+ external exposure

control



light)


+ Image quality



+ external exposure

control

- heavy (gt 500 g)



RPAS flights

26


05 pixel



compensation (FMC)





windy conditions


latency

119906 =119888 lowast 120596 lowast ∆119905

119862119862119863[micro119898]

Pa

rt II

ndash S

yste

ms amp

Se

nso

rs



RPAS flights

27


speed to keep image



time

Example


c = 9 mm


of 118degsec




Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs


Stabilized mounts

28







Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



29






landing






Quadro copter-Start


rt I-2

ndash S

yste

ms amp

Se

nso

rs



30


their environment



Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



31




navigation



bull Problems


buildings


ndash Expensive

ndash hellip



Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



32









Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



33




ndash Payload 200 g






pilot and Gimbal


Dji Phantom 2

ArduPilot Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



34


RPAS (examples)





Geo referencing




ndash FOV 100deg

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs


RPAS-laser scanning

35






FOV


than 1000 ft




parallel scan lines




RIEGL RiCOPTER

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



36

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



camera

37

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



38

φi

i

Light

source

Observer

North

φr

r

)(

)()(

ii

rriirrii

E

L

BRDF





F

D A A

B

C E G

O

Honkavaara 2014

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs

wwweurosdrnet



Michael Cramer




wwweurosdrnet








Data Acquisition

RPAS Photogrammetry

=




rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts

41





Distance


Base

xlsquo

xlsquolsquo

Accuracy parameters


ndash Base


bull Measurement

accuracy in image

space




quality


sXY

sZ


Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





Distance Z

Base B

xlsquo

xlsquolsquo

sXY

sZ

43

x X y Y

c Z c Z

x X B y Y

c Z c Z

x

c B c BZ

x x p

y yY Z Z

c c

xX Z

c


Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





Distance Z

Base B

xlsquo

xlsquolsquo



Z b x

Y X b x

Zm

B

m

s s

s s s

sXY

sZ

2

Z Z

x Z b Z

Z B

Zm

c

s s

s s s

Accuracy

44


Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



photogrammetry




xlsquo

xlsquolsquo




sXY

sZ



(analog) airborne






projects

45

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





bull Image scale



XYZ b xq ms s

Z b x

Y X b x

Zm

m

Bs s

s s s


46

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts






11 21 31

13 23 33

12 22 32

13 23 33

r X r Y r Zx z

r X r Y r Z

r X r Y r Zy z

r X r Y r Z

0

0

0

X X X

Y Y Y

Z Z Z

0

0

0

x x x

y y y

z z z c

with 11 12 13

31 32 33

r x r y r zX Z

r x r y r z

21 22 23

31 32 33

r x r y r cY Z

r x r y r c


coordinate frames



coordinates





47

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



0

0

0

X X X

Y Y Y

Z Z Z

0

0

0

x x x

y y y

z z z c


11 21 31

13 23 33

12 22 32

13 23 33

r X r Y r Zx z x

r X r Y r Z

r X r Y r Zy z y

r X r Y r Z









with

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


Camera Calibration





49

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Object coordinate

system

camera

P object point

Plsquo image point


cx

cz

cy

0X

X

)( Rp

p



X

Y

Z

0

l l l Cam

Cam X X R p

50

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




Unit cx

cz

cy

X

Y

Z

bzby

bx


0X

X

)( Rp

p

0

bX

GPS

bX

Cam

bX

e



Object coordinate

system

camera

P object point

Plsquo image point


51

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





Keep in mind





0 l l Cab b b

Ca

m


b b

Cam GPS X X

( )b

Cam R

( ) ( )l n

b b R R

52

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




close-range

53

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Standard-AT

GNSS supported AT

few control points

Calibrated cams +

self-calibration

(math models)

GNSSinertial data



FBMLSM)

RPAS

Few control points

Full in-situ camera

calibration

(physical models

GNSS (code)



(SIFT key points)

camera calibration


up of Image Block


block

Product generation

DTMDSM (Dense

Matching) amp Ortho

Transformation into


Process chain

54

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts










image




55

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




56





x1j

x2j

x3j

Xj

P1

P2

P3

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




copy R Fergus 2014

Incremental SfM

58

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Algorithm






(DLT)



60

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


ca

me

ras

points

61


Algorithm







calibration


new 3D points



triangulation


bundle adjustment

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


ca

me

ras

points

62


Algorithm







calibration


new 3D points



triangulation


bundle adjustment

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Algorithm


rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


Image Matching













64

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts











65






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


EduServ 12 (2014)


66





Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts

wwweurosdrnet



Legal Aspects



Geoinformatik


wwweurosdrnet









69









for subsequent use



rt I-4

ndash L

ega

l Asp

ects




70





rt I-4

ndash L

ega

l Asp

ects





Privacy


apply




72

Pa

rt I-4

ndash L

ega

l Asp

ects







growing


aviation background


before end 2020


73

Pa

rt I-4

ndash L

ega

l Asp

ects



Germany








(Permit required)




74

Pa

rt I-4

ndash L

ega

l Asp

ects


75



77



European Regulation

78





framework






Pa

rt I-4

ndash L

ega

l Asp

ects




79

Pa

rt I-4

ndash L

ega

l Asp

ects



3 Categories

80

Open Category


model planes

and UAS

ndash Geofencing

ndash Subcategories

in relation to

potential harm

ndash Exemption for

toys

ndash Control thru

police

Certified Category


UAS gt 25 kg

bull Certification

similar to

manned aviation

bull Pilot licence

(PPL)


Flight Operation

through Certified

Entities

Specific Category

bull Mostly for

commercial

UAS-users


bull Requirements

depend on use

of operation


Flight Operation)


Entitiesldquo

Pa

rt I-4

ndash L

ega

l Asp

ects



81

Pa

rt I-4

ndash L

ega

l Asp

ects



RPAS segments

82








rt I-4

ndash L

ega

l Asp

ects



RPAS segments









years



83

Pa

rt I-4

ndash L

ega

l Asp

ects



Photogrammetry


Pa

rt I ndash

In

trod

uctio

n amp

Motiva

tio

n



11

bull Current Status









bull Open Issues



ndash hellip

Pa

rt I ndash

In

trod

uctio

n amp

Motiva

tio

n



Photogrammetry

12

Pa

rt I-1

ndash M

otiva

tio

n amp

In

trod

uctio

n



13


corporate publicity











locations


Pa

rt I-1

ndash M

otiva

tio

n amp

In

trod

uctio

n



14

bull Real estate







parameters



mammals


movements



bull Tree diseases





bull Burial grounds













amp ash clouds



























rt I-1

ndash M

otiva

tio

n amp

In

trod

uctio

n

wwweurosdrnet



Systems amp Sensors



Geoinformatik


wwweurosdrnet








Terminology

17















Terminology

18






(CAP722 CAA UK)








UA

S S

yste

ms


Components of RPAS

19


Ground station

Avionics

Mission-

planning

Energy

supply

Data transfer

Data transfer

Propulsion and


instruments

Offline control

Imaging sensors


Control

airframe

Data


Flight segment


Mis

sio

n C

on

trol

Navigation

- Orientation

- Sensors


rt I-2

ndash S

yste

ms amp

Se

nso

rs


RPAS-Classification

20


Flight Altitude (m)

Endurance (h)

MTOW (kg)




Close Range CR 10-30 3000 2-4 150

Short Range SR 30-70 3000 3-6 200




MALE gt500 14000 24-48 1500


HALE gt2000 20000 24-48 4500-12000




van Blyenburg 2008

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs


Micro and Mini-RPAS

21

Fixed wing


Blimp

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs




22

Fixed wing

UAS UAS Model



Cost Cost + ++ + +





Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



23

bull Hand start


RPAS lt 6 kg


bull Start Catapult

ndash heavy

ndash complex

ndash dangerous

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



24

bull Net



bull Parachute



Pa

rt II

ndash S

yste

ms amp

Se

nso

rs



25

Pa

rt II

ndash S

yste

ms amp

Se

nso

rs + small




- Fish eye lens

+ small


+ external exposure

control



light)


+ Image quality



+ external exposure

control

- heavy (gt 500 g)



RPAS flights

26


05 pixel



compensation (FMC)





windy conditions


latency

119906 =119888 lowast 120596 lowast ∆119905

119862119862119863[micro119898]

Pa

rt II

ndash S

yste

ms amp

Se

nso

rs



RPAS flights

27


speed to keep image



time

Example


c = 9 mm


of 118degsec




Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs


Stabilized mounts

28







Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



29






landing






Quadro copter-Start


rt I-2

ndash S

yste

ms amp

Se

nso

rs



30


their environment



Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



31




navigation



bull Problems


buildings


ndash Expensive

ndash hellip



Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



32









Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



33




ndash Payload 200 g






pilot and Gimbal


Dji Phantom 2

ArduPilot Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



34


RPAS (examples)





Geo referencing




ndash FOV 100deg

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs


RPAS-laser scanning

35






FOV


than 1000 ft




parallel scan lines




RIEGL RiCOPTER

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



36

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



camera

37

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



38

φi

i

Light

source

Observer

North

φr

r

)(

)()(

ii

rriirrii

E

L

BRDF





F

D A A

B

C E G

O

Honkavaara 2014

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs

wwweurosdrnet



Michael Cramer




wwweurosdrnet








Data Acquisition

RPAS Photogrammetry

=




rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts

41





Distance


Base

xlsquo

xlsquolsquo

Accuracy parameters


ndash Base


bull Measurement

accuracy in image

space




quality


sXY

sZ


Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





Distance Z

Base B

xlsquo

xlsquolsquo

sXY

sZ

43

x X y Y

c Z c Z

x X B y Y

c Z c Z

x

c B c BZ

x x p

y yY Z Z

c c

xX Z

c


Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





Distance Z

Base B

xlsquo

xlsquolsquo



Z b x

Y X b x

Zm

B

m

s s

s s s

sXY

sZ

2

Z Z

x Z b Z

Z B

Zm

c

s s

s s s

Accuracy

44


Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



photogrammetry




xlsquo

xlsquolsquo




sXY

sZ



(analog) airborne






projects

45

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





bull Image scale



XYZ b xq ms s

Z b x

Y X b x

Zm

m

Bs s

s s s


46

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts






11 21 31

13 23 33

12 22 32

13 23 33

r X r Y r Zx z

r X r Y r Z

r X r Y r Zy z

r X r Y r Z

0

0

0

X X X

Y Y Y

Z Z Z

0

0

0

x x x

y y y

z z z c

with 11 12 13

31 32 33

r x r y r zX Z

r x r y r z

21 22 23

31 32 33

r x r y r cY Z

r x r y r c


coordinate frames



coordinates





47

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



0

0

0

X X X

Y Y Y

Z Z Z

0

0

0

x x x

y y y

z z z c


11 21 31

13 23 33

12 22 32

13 23 33

r X r Y r Zx z x

r X r Y r Z

r X r Y r Zy z y

r X r Y r Z









with

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


Camera Calibration





49

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Object coordinate

system

camera

P object point

Plsquo image point


cx

cz

cy

0X

X

)( Rp

p



X

Y

Z

0

l l l Cam

Cam X X R p

50

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




Unit cx

cz

cy

X

Y

Z

bzby

bx


0X

X

)( Rp

p

0

bX

GPS

bX

Cam

bX

e



Object coordinate

system

camera

P object point

Plsquo image point


51

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





Keep in mind





0 l l Cab b b

Ca

m


b b

Cam GPS X X

( )b

Cam R

( ) ( )l n

b b R R

52

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




close-range

53

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Standard-AT

GNSS supported AT

few control points

Calibrated cams +

self-calibration

(math models)

GNSSinertial data



FBMLSM)

RPAS

Few control points

Full in-situ camera

calibration

(physical models

GNSS (code)



(SIFT key points)

camera calibration


up of Image Block


block

Product generation

DTMDSM (Dense

Matching) amp Ortho

Transformation into


Process chain

54

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts










image




55

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




56





x1j

x2j

x3j

Xj

P1

P2

P3

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




copy R Fergus 2014

Incremental SfM

58

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Algorithm






(DLT)



60

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


ca

me

ras

points

61


Algorithm







calibration


new 3D points



triangulation


bundle adjustment

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


ca

me

ras

points

62


Algorithm







calibration


new 3D points



triangulation


bundle adjustment

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Algorithm


rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


Image Matching













64

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts











65






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


EduServ 12 (2014)


66





Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts

wwweurosdrnet



Legal Aspects



Geoinformatik


wwweurosdrnet









69









for subsequent use



rt I-4

ndash L

ega

l Asp

ects




70





rt I-4

ndash L

ega

l Asp

ects





Privacy


apply




72

Pa

rt I-4

ndash L

ega

l Asp

ects







growing


aviation background


before end 2020


73

Pa

rt I-4

ndash L

ega

l Asp

ects



Germany








(Permit required)




74

Pa

rt I-4

ndash L

ega

l Asp

ects


75



77



European Regulation

78





framework






Pa

rt I-4

ndash L

ega

l Asp

ects




79

Pa

rt I-4

ndash L

ega

l Asp

ects



3 Categories

80

Open Category


model planes

and UAS

ndash Geofencing

ndash Subcategories

in relation to

potential harm

ndash Exemption for

toys

ndash Control thru

police

Certified Category


UAS gt 25 kg

bull Certification

similar to

manned aviation

bull Pilot licence

(PPL)


Flight Operation

through Certified

Entities

Specific Category

bull Mostly for

commercial

UAS-users


bull Requirements

depend on use

of operation


Flight Operation)


Entitiesldquo

Pa

rt I-4

ndash L

ega

l Asp

ects



81

Pa

rt I-4

ndash L

ega

l Asp

ects



RPAS segments

82








rt I-4

ndash L

ega

l Asp

ects



RPAS segments









years



83

Pa

rt I-4

ndash L

ega

l Asp

ects



11

bull Current Status









bull Open Issues



ndash hellip

Pa

rt I ndash

In

trod

uctio

n amp

Motiva

tio

n



Photogrammetry

12

Pa

rt I-1

ndash M

otiva

tio

n amp

In

trod

uctio

n



13


corporate publicity











locations


Pa

rt I-1

ndash M

otiva

tio

n amp

In

trod

uctio

n



14

bull Real estate







parameters



mammals


movements



bull Tree diseases





bull Burial grounds













amp ash clouds



























rt I-1

ndash M

otiva

tio

n amp

In

trod

uctio

n

wwweurosdrnet



Systems amp Sensors



Geoinformatik


wwweurosdrnet








Terminology

17















Terminology

18






(CAP722 CAA UK)








UA

S S

yste

ms


Components of RPAS

19


Ground station

Avionics

Mission-

planning

Energy

supply

Data transfer

Data transfer

Propulsion and


instruments

Offline control

Imaging sensors


Control

airframe

Data


Flight segment


Mis

sio

n C

on

trol

Navigation

- Orientation

- Sensors


rt I-2

ndash S

yste

ms amp

Se

nso

rs


RPAS-Classification

20


Flight Altitude (m)

Endurance (h)

MTOW (kg)




Close Range CR 10-30 3000 2-4 150

Short Range SR 30-70 3000 3-6 200




MALE gt500 14000 24-48 1500


HALE gt2000 20000 24-48 4500-12000




van Blyenburg 2008

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs


Micro and Mini-RPAS

21

Fixed wing


Blimp

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs




22

Fixed wing

UAS UAS Model



Cost Cost + ++ + +





Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



23

bull Hand start


RPAS lt 6 kg


bull Start Catapult

ndash heavy

ndash complex

ndash dangerous

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



24

bull Net



bull Parachute



Pa

rt II

ndash S

yste

ms amp

Se

nso

rs



25

Pa

rt II

ndash S

yste

ms amp

Se

nso

rs + small




- Fish eye lens

+ small


+ external exposure

control



light)


+ Image quality



+ external exposure

control

- heavy (gt 500 g)



RPAS flights

26


05 pixel



compensation (FMC)





windy conditions


latency

119906 =119888 lowast 120596 lowast ∆119905

119862119862119863[micro119898]

Pa

rt II

ndash S

yste

ms amp

Se

nso

rs



RPAS flights

27


speed to keep image



time

Example


c = 9 mm


of 118degsec




Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs


Stabilized mounts

28







Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



29






landing






Quadro copter-Start


rt I-2

ndash S

yste

ms amp

Se

nso

rs



30


their environment



Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



31




navigation



bull Problems


buildings


ndash Expensive

ndash hellip



Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



32









Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



33




ndash Payload 200 g






pilot and Gimbal


Dji Phantom 2

ArduPilot Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



34


RPAS (examples)





Geo referencing




ndash FOV 100deg

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs


RPAS-laser scanning

35






FOV


than 1000 ft




parallel scan lines




RIEGL RiCOPTER

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



36

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



camera

37

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



38

φi

i

Light

source

Observer

North

φr

r

)(

)()(

ii

rriirrii

E

L

BRDF





F

D A A

B

C E G

O

Honkavaara 2014

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs

wwweurosdrnet



Michael Cramer




wwweurosdrnet








Data Acquisition

RPAS Photogrammetry

=




rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts

41





Distance


Base

xlsquo

xlsquolsquo

Accuracy parameters


ndash Base


bull Measurement

accuracy in image

space




quality


sXY

sZ


Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





Distance Z

Base B

xlsquo

xlsquolsquo

sXY

sZ

43

x X y Y

c Z c Z

x X B y Y

c Z c Z

x

c B c BZ

x x p

y yY Z Z

c c

xX Z

c


Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





Distance Z

Base B

xlsquo

xlsquolsquo



Z b x

Y X b x

Zm

B

m

s s

s s s

sXY

sZ

2

Z Z

x Z b Z

Z B

Zm

c

s s

s s s

Accuracy

44


Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



photogrammetry




xlsquo

xlsquolsquo




sXY

sZ



(analog) airborne






projects

45

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





bull Image scale



XYZ b xq ms s

Z b x

Y X b x

Zm

m

Bs s

s s s


46

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts






11 21 31

13 23 33

12 22 32

13 23 33

r X r Y r Zx z

r X r Y r Z

r X r Y r Zy z

r X r Y r Z

0

0

0

X X X

Y Y Y

Z Z Z

0

0

0

x x x

y y y

z z z c

with 11 12 13

31 32 33

r x r y r zX Z

r x r y r z

21 22 23

31 32 33

r x r y r cY Z

r x r y r c


coordinate frames



coordinates





47

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



0

0

0

X X X

Y Y Y

Z Z Z

0

0

0

x x x

y y y

z z z c


11 21 31

13 23 33

12 22 32

13 23 33

r X r Y r Zx z x

r X r Y r Z

r X r Y r Zy z y

r X r Y r Z









with

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


Camera Calibration





49

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Object coordinate

system

camera

P object point

Plsquo image point


cx

cz

cy

0X

X

)( Rp

p



X

Y

Z

0

l l l Cam

Cam X X R p

50

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




Unit cx

cz

cy

X

Y

Z

bzby

bx


0X

X

)( Rp

p

0

bX

GPS

bX

Cam

bX

e



Object coordinate

system

camera

P object point

Plsquo image point


51

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





Keep in mind





0 l l Cab b b

Ca

m


b b

Cam GPS X X

( )b

Cam R

( ) ( )l n

b b R R

52

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




close-range

53

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Standard-AT

GNSS supported AT

few control points

Calibrated cams +

self-calibration

(math models)

GNSSinertial data



FBMLSM)

RPAS

Few control points

Full in-situ camera

calibration

(physical models

GNSS (code)



(SIFT key points)

camera calibration


up of Image Block


block

Product generation

DTMDSM (Dense

Matching) amp Ortho

Transformation into


Process chain

54

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts










image




55

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




56





x1j

x2j

x3j

Xj

P1

P2

P3

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




copy R Fergus 2014

Incremental SfM

58

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Algorithm






(DLT)



60

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


ca

me

ras

points

61


Algorithm







calibration


new 3D points



triangulation


bundle adjustment

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


ca

me

ras

points

62


Algorithm







calibration


new 3D points



triangulation


bundle adjustment

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Algorithm


rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


Image Matching













64

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts











65






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


EduServ 12 (2014)


66





Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts

wwweurosdrnet



Legal Aspects



Geoinformatik


wwweurosdrnet









69









for subsequent use



rt I-4

ndash L

ega

l Asp

ects




70





rt I-4

ndash L

ega

l Asp

ects





Privacy


apply




72

Pa

rt I-4

ndash L

ega

l Asp

ects







growing


aviation background


before end 2020


73

Pa

rt I-4

ndash L

ega

l Asp

ects



Germany








(Permit required)




74

Pa

rt I-4

ndash L

ega

l Asp

ects


75



77



European Regulation

78





framework






Pa

rt I-4

ndash L

ega

l Asp

ects




79

Pa

rt I-4

ndash L

ega

l Asp

ects



3 Categories

80

Open Category


model planes

and UAS

ndash Geofencing

ndash Subcategories

in relation to

potential harm

ndash Exemption for

toys

ndash Control thru

police

Certified Category


UAS gt 25 kg

bull Certification

similar to

manned aviation

bull Pilot licence

(PPL)


Flight Operation

through Certified

Entities

Specific Category

bull Mostly for

commercial

UAS-users


bull Requirements

depend on use

of operation


Flight Operation)


Entitiesldquo

Pa

rt I-4

ndash L

ega

l Asp

ects



81

Pa

rt I-4

ndash L

ega

l Asp

ects



RPAS segments

82








rt I-4

ndash L

ega

l Asp

ects



RPAS segments









years



83

Pa

rt I-4

ndash L

ega

l Asp

ects



Photogrammetry

12

Pa

rt I-1

ndash M

otiva

tio

n amp

In

trod

uctio

n



13


corporate publicity











locations


Pa

rt I-1

ndash M

otiva

tio

n amp

In

trod

uctio

n



14

bull Real estate







parameters



mammals


movements



bull Tree diseases





bull Burial grounds













amp ash clouds



























rt I-1

ndash M

otiva

tio

n amp

In

trod

uctio

n

wwweurosdrnet



Systems amp Sensors



Geoinformatik


wwweurosdrnet








Terminology

17















Terminology

18






(CAP722 CAA UK)








UA

S S

yste

ms


Components of RPAS

19


Ground station

Avionics

Mission-

planning

Energy

supply

Data transfer

Data transfer

Propulsion and


instruments

Offline control

Imaging sensors


Control

airframe

Data


Flight segment


Mis

sio

n C

on

trol

Navigation

- Orientation

- Sensors


rt I-2

ndash S

yste

ms amp

Se

nso

rs


RPAS-Classification

20


Flight Altitude (m)

Endurance (h)

MTOW (kg)




Close Range CR 10-30 3000 2-4 150

Short Range SR 30-70 3000 3-6 200




MALE gt500 14000 24-48 1500


HALE gt2000 20000 24-48 4500-12000




van Blyenburg 2008

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs


Micro and Mini-RPAS

21

Fixed wing


Blimp

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs




22

Fixed wing

UAS UAS Model



Cost Cost + ++ + +





Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



23

bull Hand start


RPAS lt 6 kg


bull Start Catapult

ndash heavy

ndash complex

ndash dangerous

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



24

bull Net



bull Parachute



Pa

rt II

ndash S

yste

ms amp

Se

nso

rs



25

Pa

rt II

ndash S

yste

ms amp

Se

nso

rs + small




- Fish eye lens

+ small


+ external exposure

control



light)


+ Image quality



+ external exposure

control

- heavy (gt 500 g)



RPAS flights

26


05 pixel



compensation (FMC)





windy conditions


latency

119906 =119888 lowast 120596 lowast ∆119905

119862119862119863[micro119898]

Pa

rt II

ndash S

yste

ms amp

Se

nso

rs



RPAS flights

27


speed to keep image



time

Example


c = 9 mm


of 118degsec




Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs


Stabilized mounts

28







Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



29






landing






Quadro copter-Start


rt I-2

ndash S

yste

ms amp

Se

nso

rs



30


their environment



Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



31




navigation



bull Problems


buildings


ndash Expensive

ndash hellip



Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



32









Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



33




ndash Payload 200 g






pilot and Gimbal


Dji Phantom 2

ArduPilot Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



34


RPAS (examples)





Geo referencing




ndash FOV 100deg

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs


RPAS-laser scanning

35






FOV


than 1000 ft




parallel scan lines




RIEGL RiCOPTER

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



36

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



camera

37

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



38

φi

i

Light

source

Observer

North

φr

r

)(

)()(

ii

rriirrii

E

L

BRDF





F

D A A

B

C E G

O

Honkavaara 2014

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs

wwweurosdrnet



Michael Cramer




wwweurosdrnet








Data Acquisition

RPAS Photogrammetry

=




rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts

41





Distance


Base

xlsquo

xlsquolsquo

Accuracy parameters


ndash Base


bull Measurement

accuracy in image

space




quality


sXY

sZ


Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





Distance Z

Base B

xlsquo

xlsquolsquo

sXY

sZ

43

x X y Y

c Z c Z

x X B y Y

c Z c Z

x

c B c BZ

x x p

y yY Z Z

c c

xX Z

c


Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





Distance Z

Base B

xlsquo

xlsquolsquo



Z b x

Y X b x

Zm

B

m

s s

s s s

sXY

sZ

2

Z Z

x Z b Z

Z B

Zm

c

s s

s s s

Accuracy

44


Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



photogrammetry




xlsquo

xlsquolsquo




sXY

sZ



(analog) airborne






projects

45

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





bull Image scale



XYZ b xq ms s

Z b x

Y X b x

Zm

m

Bs s

s s s


46

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts






11 21 31

13 23 33

12 22 32

13 23 33

r X r Y r Zx z

r X r Y r Z

r X r Y r Zy z

r X r Y r Z

0

0

0

X X X

Y Y Y

Z Z Z

0

0

0

x x x

y y y

z z z c

with 11 12 13

31 32 33

r x r y r zX Z

r x r y r z

21 22 23

31 32 33

r x r y r cY Z

r x r y r c


coordinate frames



coordinates





47

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



0

0

0

X X X

Y Y Y

Z Z Z

0

0

0

x x x

y y y

z z z c


11 21 31

13 23 33

12 22 32

13 23 33

r X r Y r Zx z x

r X r Y r Z

r X r Y r Zy z y

r X r Y r Z









with

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


Camera Calibration





49

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Object coordinate

system

camera

P object point

Plsquo image point


cx

cz

cy

0X

X

)( Rp

p



X

Y

Z

0

l l l Cam

Cam X X R p

50

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




Unit cx

cz

cy

X

Y

Z

bzby

bx


0X

X

)( Rp

p

0

bX

GPS

bX

Cam

bX

e



Object coordinate

system

camera

P object point

Plsquo image point


51

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





Keep in mind





0 l l Cab b b

Ca

m


b b

Cam GPS X X

( )b

Cam R

( ) ( )l n

b b R R

52

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




close-range

53

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Standard-AT

GNSS supported AT

few control points

Calibrated cams +

self-calibration

(math models)

GNSSinertial data



FBMLSM)

RPAS

Few control points

Full in-situ camera

calibration

(physical models

GNSS (code)



(SIFT key points)

camera calibration


up of Image Block


block

Product generation

DTMDSM (Dense

Matching) amp Ortho

Transformation into


Process chain

54

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts










image




55

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




56





x1j

x2j

x3j

Xj

P1

P2

P3

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




copy R Fergus 2014

Incremental SfM

58

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Algorithm






(DLT)



60

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


ca

me

ras

points

61


Algorithm







calibration


new 3D points



triangulation


bundle adjustment

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


ca

me

ras

points

62


Algorithm







calibration


new 3D points



triangulation


bundle adjustment

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Algorithm


rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


Image Matching













64

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts











65






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


EduServ 12 (2014)


66





Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts

wwweurosdrnet



Legal Aspects



Geoinformatik


wwweurosdrnet









69









for subsequent use



rt I-4

ndash L

ega

l Asp

ects




70





rt I-4

ndash L

ega

l Asp

ects





Privacy


apply




72

Pa

rt I-4

ndash L

ega

l Asp

ects







growing


aviation background


before end 2020


73

Pa

rt I-4

ndash L

ega

l Asp

ects



Germany








(Permit required)




74

Pa

rt I-4

ndash L

ega

l Asp

ects


75



77



European Regulation

78





framework






Pa

rt I-4

ndash L

ega

l Asp

ects




79

Pa

rt I-4

ndash L

ega

l Asp

ects



3 Categories

80

Open Category


model planes

and UAS

ndash Geofencing

ndash Subcategories

in relation to

potential harm

ndash Exemption for

toys

ndash Control thru

police

Certified Category


UAS gt 25 kg

bull Certification

similar to

manned aviation

bull Pilot licence

(PPL)


Flight Operation

through Certified

Entities

Specific Category

bull Mostly for

commercial

UAS-users


bull Requirements

depend on use

of operation


Flight Operation)


Entitiesldquo

Pa

rt I-4

ndash L

ega

l Asp

ects



81

Pa

rt I-4

ndash L

ega

l Asp

ects



RPAS segments

82








rt I-4

ndash L

ega

l Asp

ects



RPAS segments









years



83

Pa

rt I-4

ndash L

ega

l Asp

ects



13


corporate publicity











locations


Pa

rt I-1

ndash M

otiva

tio

n amp

In

trod

uctio

n



14

bull Real estate







parameters



mammals


movements



bull Tree diseases





bull Burial grounds













amp ash clouds



























rt I-1

ndash M

otiva

tio

n amp

In

trod

uctio

n

wwweurosdrnet



Systems amp Sensors



Geoinformatik


wwweurosdrnet








Terminology

17















Terminology

18






(CAP722 CAA UK)








UA

S S

yste

ms


Components of RPAS

19


Ground station

Avionics

Mission-

planning

Energy

supply

Data transfer

Data transfer

Propulsion and


instruments

Offline control

Imaging sensors


Control

airframe

Data


Flight segment


Mis

sio

n C

on

trol

Navigation

- Orientation

- Sensors


rt I-2

ndash S

yste

ms amp

Se

nso

rs


RPAS-Classification

20


Flight Altitude (m)

Endurance (h)

MTOW (kg)




Close Range CR 10-30 3000 2-4 150

Short Range SR 30-70 3000 3-6 200




MALE gt500 14000 24-48 1500


HALE gt2000 20000 24-48 4500-12000




van Blyenburg 2008

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs


Micro and Mini-RPAS

21

Fixed wing


Blimp

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs




22

Fixed wing

UAS UAS Model



Cost Cost + ++ + +





Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



23

bull Hand start


RPAS lt 6 kg


bull Start Catapult

ndash heavy

ndash complex

ndash dangerous

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



24

bull Net



bull Parachute



Pa

rt II

ndash S

yste

ms amp

Se

nso

rs



25

Pa

rt II

ndash S

yste

ms amp

Se

nso

rs + small




- Fish eye lens

+ small


+ external exposure

control



light)


+ Image quality



+ external exposure

control

- heavy (gt 500 g)



RPAS flights

26


05 pixel



compensation (FMC)





windy conditions


latency

119906 =119888 lowast 120596 lowast ∆119905

119862119862119863[micro119898]

Pa

rt II

ndash S

yste

ms amp

Se

nso

rs



RPAS flights

27


speed to keep image



time

Example


c = 9 mm


of 118degsec




Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs


Stabilized mounts

28







Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



29






landing






Quadro copter-Start


rt I-2

ndash S

yste

ms amp

Se

nso

rs



30


their environment



Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



31




navigation



bull Problems


buildings


ndash Expensive

ndash hellip



Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



32









Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



33




ndash Payload 200 g






pilot and Gimbal


Dji Phantom 2

ArduPilot Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



34


RPAS (examples)





Geo referencing




ndash FOV 100deg

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs


RPAS-laser scanning

35






FOV


than 1000 ft




parallel scan lines




RIEGL RiCOPTER

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



36

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



camera

37

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



38

φi

i

Light

source

Observer

North

φr

r

)(

)()(

ii

rriirrii

E

L

BRDF





F

D A A

B

C E G

O

Honkavaara 2014

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs

wwweurosdrnet



Michael Cramer




wwweurosdrnet








Data Acquisition

RPAS Photogrammetry

=




rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts

41





Distance


Base

xlsquo

xlsquolsquo

Accuracy parameters


ndash Base


bull Measurement

accuracy in image

space




quality


sXY

sZ


Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





Distance Z

Base B

xlsquo

xlsquolsquo

sXY

sZ

43

x X y Y

c Z c Z

x X B y Y

c Z c Z

x

c B c BZ

x x p

y yY Z Z

c c

xX Z

c


Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





Distance Z

Base B

xlsquo

xlsquolsquo



Z b x

Y X b x

Zm

B

m

s s

s s s

sXY

sZ

2

Z Z

x Z b Z

Z B

Zm

c

s s

s s s

Accuracy

44


Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



photogrammetry




xlsquo

xlsquolsquo




sXY

sZ



(analog) airborne






projects

45

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





bull Image scale



XYZ b xq ms s

Z b x

Y X b x

Zm

m

Bs s

s s s


46

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts






11 21 31

13 23 33

12 22 32

13 23 33

r X r Y r Zx z

r X r Y r Z

r X r Y r Zy z

r X r Y r Z

0

0

0

X X X

Y Y Y

Z Z Z

0

0

0

x x x

y y y

z z z c

with 11 12 13

31 32 33

r x r y r zX Z

r x r y r z

21 22 23

31 32 33

r x r y r cY Z

r x r y r c


coordinate frames



coordinates





47

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



0

0

0

X X X

Y Y Y

Z Z Z

0

0

0

x x x

y y y

z z z c


11 21 31

13 23 33

12 22 32

13 23 33

r X r Y r Zx z x

r X r Y r Z

r X r Y r Zy z y

r X r Y r Z









with

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


Camera Calibration





49

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Object coordinate

system

camera

P object point

Plsquo image point


cx

cz

cy

0X

X

)( Rp

p



X

Y

Z

0

l l l Cam

Cam X X R p

50

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




Unit cx

cz

cy

X

Y

Z

bzby

bx


0X

X

)( Rp

p

0

bX

GPS

bX

Cam

bX

e



Object coordinate

system

camera

P object point

Plsquo image point


51

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





Keep in mind





0 l l Cab b b

Ca

m


b b

Cam GPS X X

( )b

Cam R

( ) ( )l n

b b R R

52

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




close-range

53

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Standard-AT

GNSS supported AT

few control points

Calibrated cams +

self-calibration

(math models)

GNSSinertial data



FBMLSM)

RPAS

Few control points

Full in-situ camera

calibration

(physical models

GNSS (code)



(SIFT key points)

camera calibration


up of Image Block


block

Product generation

DTMDSM (Dense

Matching) amp Ortho

Transformation into


Process chain

54

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts










image




55

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




56





x1j

x2j

x3j

Xj

P1

P2

P3

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




copy R Fergus 2014

Incremental SfM

58

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Algorithm






(DLT)



60

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


ca

me

ras

points

61


Algorithm







calibration


new 3D points



triangulation


bundle adjustment

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


ca

me

ras

points

62


Algorithm







calibration


new 3D points



triangulation


bundle adjustment

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Algorithm


rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


Image Matching













64

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts











65






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


EduServ 12 (2014)


66





Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts

wwweurosdrnet



Legal Aspects



Geoinformatik


wwweurosdrnet









69









for subsequent use



rt I-4

ndash L

ega

l Asp

ects




70





rt I-4

ndash L

ega

l Asp

ects





Privacy


apply




72

Pa

rt I-4

ndash L

ega

l Asp

ects







growing


aviation background


before end 2020


73

Pa

rt I-4

ndash L

ega

l Asp

ects



Germany








(Permit required)




74

Pa

rt I-4

ndash L

ega

l Asp

ects


75



77



European Regulation

78





framework






Pa

rt I-4

ndash L

ega

l Asp

ects




79

Pa

rt I-4

ndash L

ega

l Asp

ects



3 Categories

80

Open Category


model planes

and UAS

ndash Geofencing

ndash Subcategories

in relation to

potential harm

ndash Exemption for

toys

ndash Control thru

police

Certified Category


UAS gt 25 kg

bull Certification

similar to

manned aviation

bull Pilot licence

(PPL)


Flight Operation

through Certified

Entities

Specific Category

bull Mostly for

commercial

UAS-users


bull Requirements

depend on use

of operation


Flight Operation)


Entitiesldquo

Pa

rt I-4

ndash L

ega

l Asp

ects



81

Pa

rt I-4

ndash L

ega

l Asp

ects



RPAS segments

82








rt I-4

ndash L

ega

l Asp

ects



RPAS segments









years



83

Pa

rt I-4

ndash L

ega

l Asp

ects



14

bull Real estate







parameters



mammals


movements



bull Tree diseases





bull Burial grounds













amp ash clouds



























rt I-1

ndash M

otiva

tio

n amp

In

trod

uctio

n

wwweurosdrnet



Systems amp Sensors



Geoinformatik


wwweurosdrnet








Terminology

17















Terminology

18






(CAP722 CAA UK)








UA

S S

yste

ms


Components of RPAS

19


Ground station

Avionics

Mission-

planning

Energy

supply

Data transfer

Data transfer

Propulsion and


instruments

Offline control

Imaging sensors


Control

airframe

Data


Flight segment


Mis

sio

n C

on

trol

Navigation

- Orientation

- Sensors


rt I-2

ndash S

yste

ms amp

Se

nso

rs


RPAS-Classification

20


Flight Altitude (m)

Endurance (h)

MTOW (kg)




Close Range CR 10-30 3000 2-4 150

Short Range SR 30-70 3000 3-6 200




MALE gt500 14000 24-48 1500


HALE gt2000 20000 24-48 4500-12000




van Blyenburg 2008

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs


Micro and Mini-RPAS

21

Fixed wing


Blimp

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs




22

Fixed wing

UAS UAS Model



Cost Cost + ++ + +





Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



23

bull Hand start


RPAS lt 6 kg


bull Start Catapult

ndash heavy

ndash complex

ndash dangerous

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



24

bull Net



bull Parachute



Pa

rt II

ndash S

yste

ms amp

Se

nso

rs



25

Pa

rt II

ndash S

yste

ms amp

Se

nso

rs + small




- Fish eye lens

+ small


+ external exposure

control



light)


+ Image quality



+ external exposure

control

- heavy (gt 500 g)



RPAS flights

26


05 pixel



compensation (FMC)





windy conditions


latency

119906 =119888 lowast 120596 lowast ∆119905

119862119862119863[micro119898]

Pa

rt II

ndash S

yste

ms amp

Se

nso

rs



RPAS flights

27


speed to keep image



time

Example


c = 9 mm


of 118degsec




Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs


Stabilized mounts

28







Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



29






landing






Quadro copter-Start


rt I-2

ndash S

yste

ms amp

Se

nso

rs



30


their environment



Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



31




navigation



bull Problems


buildings


ndash Expensive

ndash hellip



Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



32









Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



33




ndash Payload 200 g






pilot and Gimbal


Dji Phantom 2

ArduPilot Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



34


RPAS (examples)





Geo referencing




ndash FOV 100deg

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs


RPAS-laser scanning

35






FOV


than 1000 ft




parallel scan lines




RIEGL RiCOPTER

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



36

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



camera

37

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



38

φi

i

Light

source

Observer

North

φr

r

)(

)()(

ii

rriirrii

E

L

BRDF





F

D A A

B

C E G

O

Honkavaara 2014

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs

wwweurosdrnet



Michael Cramer




wwweurosdrnet








Data Acquisition

RPAS Photogrammetry

=




rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts

41





Distance


Base

xlsquo

xlsquolsquo

Accuracy parameters


ndash Base


bull Measurement

accuracy in image

space




quality


sXY

sZ


Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





Distance Z

Base B

xlsquo

xlsquolsquo

sXY

sZ

43

x X y Y

c Z c Z

x X B y Y

c Z c Z

x

c B c BZ

x x p

y yY Z Z

c c

xX Z

c


Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





Distance Z

Base B

xlsquo

xlsquolsquo



Z b x

Y X b x

Zm

B

m

s s

s s s

sXY

sZ

2

Z Z

x Z b Z

Z B

Zm

c

s s

s s s

Accuracy

44


Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



photogrammetry




xlsquo

xlsquolsquo




sXY

sZ



(analog) airborne






projects

45

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





bull Image scale



XYZ b xq ms s

Z b x

Y X b x

Zm

m

Bs s

s s s


46

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts






11 21 31

13 23 33

12 22 32

13 23 33

r X r Y r Zx z

r X r Y r Z

r X r Y r Zy z

r X r Y r Z

0

0

0

X X X

Y Y Y

Z Z Z

0

0

0

x x x

y y y

z z z c

with 11 12 13

31 32 33

r x r y r zX Z

r x r y r z

21 22 23

31 32 33

r x r y r cY Z

r x r y r c


coordinate frames



coordinates





47

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



0

0

0

X X X

Y Y Y

Z Z Z

0

0

0

x x x

y y y

z z z c


11 21 31

13 23 33

12 22 32

13 23 33

r X r Y r Zx z x

r X r Y r Z

r X r Y r Zy z y

r X r Y r Z









with

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


Camera Calibration





49

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Object coordinate

system

camera

P object point

Plsquo image point


cx

cz

cy

0X

X

)( Rp

p



X

Y

Z

0

l l l Cam

Cam X X R p

50

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




Unit cx

cz

cy

X

Y

Z

bzby

bx


0X

X

)( Rp

p

0

bX

GPS

bX

Cam

bX

e



Object coordinate

system

camera

P object point

Plsquo image point


51

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





Keep in mind





0 l l Cab b b

Ca

m


b b

Cam GPS X X

( )b

Cam R

( ) ( )l n

b b R R

52

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




close-range

53

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Standard-AT

GNSS supported AT

few control points

Calibrated cams +

self-calibration

(math models)

GNSSinertial data



FBMLSM)

RPAS

Few control points

Full in-situ camera

calibration

(physical models

GNSS (code)



(SIFT key points)

camera calibration


up of Image Block


block

Product generation

DTMDSM (Dense

Matching) amp Ortho

Transformation into


Process chain

54

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts










image




55

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




56





x1j

x2j

x3j

Xj

P1

P2

P3

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




copy R Fergus 2014

Incremental SfM

58

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Algorithm






(DLT)



60

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


ca

me

ras

points

61


Algorithm







calibration


new 3D points



triangulation


bundle adjustment

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


ca

me

ras

points

62


Algorithm







calibration


new 3D points



triangulation


bundle adjustment

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Algorithm


rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


Image Matching













64

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts











65






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


EduServ 12 (2014)


66





Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts

wwweurosdrnet



Legal Aspects



Geoinformatik


wwweurosdrnet









69









for subsequent use



rt I-4

ndash L

ega

l Asp

ects




70





rt I-4

ndash L

ega

l Asp

ects





Privacy


apply




72

Pa

rt I-4

ndash L

ega

l Asp

ects







growing


aviation background


before end 2020


73

Pa

rt I-4

ndash L

ega

l Asp

ects



Germany








(Permit required)




74

Pa

rt I-4

ndash L

ega

l Asp

ects


75



77



European Regulation

78





framework






Pa

rt I-4

ndash L

ega

l Asp

ects




79

Pa

rt I-4

ndash L

ega

l Asp

ects



3 Categories

80

Open Category


model planes

and UAS

ndash Geofencing

ndash Subcategories

in relation to

potential harm

ndash Exemption for

toys

ndash Control thru

police

Certified Category


UAS gt 25 kg

bull Certification

similar to

manned aviation

bull Pilot licence

(PPL)


Flight Operation

through Certified

Entities

Specific Category

bull Mostly for

commercial

UAS-users


bull Requirements

depend on use

of operation


Flight Operation)


Entitiesldquo

Pa

rt I-4

ndash L

ega

l Asp

ects



81

Pa

rt I-4

ndash L

ega

l Asp

ects



RPAS segments

82








rt I-4

ndash L

ega

l Asp

ects



RPAS segments









years



83

Pa

rt I-4

ndash L

ega

l Asp

ects

wwweurosdrnet



Systems amp Sensors



Geoinformatik


wwweurosdrnet








Terminology

17















Terminology

18






(CAP722 CAA UK)








UA

S S

yste

ms


Components of RPAS

19


Ground station

Avionics

Mission-

planning

Energy

supply

Data transfer

Data transfer

Propulsion and


instruments

Offline control

Imaging sensors


Control

airframe

Data


Flight segment


Mis

sio

n C

on

trol

Navigation

- Orientation

- Sensors


rt I-2

ndash S

yste

ms amp

Se

nso

rs


RPAS-Classification

20


Flight Altitude (m)

Endurance (h)

MTOW (kg)




Close Range CR 10-30 3000 2-4 150

Short Range SR 30-70 3000 3-6 200




MALE gt500 14000 24-48 1500


HALE gt2000 20000 24-48 4500-12000




van Blyenburg 2008

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs


Micro and Mini-RPAS

21

Fixed wing


Blimp

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs




22

Fixed wing

UAS UAS Model



Cost Cost + ++ + +





Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



23

bull Hand start


RPAS lt 6 kg


bull Start Catapult

ndash heavy

ndash complex

ndash dangerous

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



24

bull Net



bull Parachute



Pa

rt II

ndash S

yste

ms amp

Se

nso

rs



25

Pa

rt II

ndash S

yste

ms amp

Se

nso

rs + small




- Fish eye lens

+ small


+ external exposure

control



light)


+ Image quality



+ external exposure

control

- heavy (gt 500 g)



RPAS flights

26


05 pixel



compensation (FMC)





windy conditions


latency

119906 =119888 lowast 120596 lowast ∆119905

119862119862119863[micro119898]

Pa

rt II

ndash S

yste

ms amp

Se

nso

rs



RPAS flights

27


speed to keep image



time

Example


c = 9 mm


of 118degsec




Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs


Stabilized mounts

28







Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



29






landing






Quadro copter-Start


rt I-2

ndash S

yste

ms amp

Se

nso

rs



30


their environment



Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



31




navigation



bull Problems


buildings


ndash Expensive

ndash hellip



Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



32









Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



33




ndash Payload 200 g






pilot and Gimbal


Dji Phantom 2

ArduPilot Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



34


RPAS (examples)





Geo referencing




ndash FOV 100deg

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs


RPAS-laser scanning

35






FOV


than 1000 ft




parallel scan lines




RIEGL RiCOPTER

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



36

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



camera

37

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



38

φi

i

Light

source

Observer

North

φr

r

)(

)()(

ii

rriirrii

E

L

BRDF





F

D A A

B

C E G

O

Honkavaara 2014

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs

wwweurosdrnet



Michael Cramer




wwweurosdrnet








Data Acquisition

RPAS Photogrammetry

=




rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts

41





Distance


Base

xlsquo

xlsquolsquo

Accuracy parameters


ndash Base


bull Measurement

accuracy in image

space




quality


sXY

sZ


Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





Distance Z

Base B

xlsquo

xlsquolsquo

sXY

sZ

43

x X y Y

c Z c Z

x X B y Y

c Z c Z

x

c B c BZ

x x p

y yY Z Z

c c

xX Z

c


Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





Distance Z

Base B

xlsquo

xlsquolsquo



Z b x

Y X b x

Zm

B

m

s s

s s s

sXY

sZ

2

Z Z

x Z b Z

Z B

Zm

c

s s

s s s

Accuracy

44


Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



photogrammetry




xlsquo

xlsquolsquo




sXY

sZ



(analog) airborne






projects

45

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





bull Image scale



XYZ b xq ms s

Z b x

Y X b x

Zm

m

Bs s

s s s


46

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts






11 21 31

13 23 33

12 22 32

13 23 33

r X r Y r Zx z

r X r Y r Z

r X r Y r Zy z

r X r Y r Z

0

0

0

X X X

Y Y Y

Z Z Z

0

0

0

x x x

y y y

z z z c

with 11 12 13

31 32 33

r x r y r zX Z

r x r y r z

21 22 23

31 32 33

r x r y r cY Z

r x r y r c


coordinate frames



coordinates





47

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



0

0

0

X X X

Y Y Y

Z Z Z

0

0

0

x x x

y y y

z z z c


11 21 31

13 23 33

12 22 32

13 23 33

r X r Y r Zx z x

r X r Y r Z

r X r Y r Zy z y

r X r Y r Z









with

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


Camera Calibration





49

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Object coordinate

system

camera

P object point

Plsquo image point


cx

cz

cy

0X

X

)( Rp

p



X

Y

Z

0

l l l Cam

Cam X X R p

50

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




Unit cx

cz

cy

X

Y

Z

bzby

bx


0X

X

)( Rp

p

0

bX

GPS

bX

Cam

bX

e



Object coordinate

system

camera

P object point

Plsquo image point


51

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





Keep in mind





0 l l Cab b b

Ca

m


b b

Cam GPS X X

( )b

Cam R

( ) ( )l n

b b R R

52

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




close-range

53

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Standard-AT

GNSS supported AT

few control points

Calibrated cams +

self-calibration

(math models)

GNSSinertial data



FBMLSM)

RPAS

Few control points

Full in-situ camera

calibration

(physical models

GNSS (code)



(SIFT key points)

camera calibration


up of Image Block


block

Product generation

DTMDSM (Dense

Matching) amp Ortho

Transformation into


Process chain

54

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts










image




55

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




56





x1j

x2j

x3j

Xj

P1

P2

P3

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




copy R Fergus 2014

Incremental SfM

58

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Algorithm






(DLT)



60

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


ca

me

ras

points

61


Algorithm







calibration


new 3D points



triangulation


bundle adjustment

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


ca

me

ras

points

62


Algorithm







calibration


new 3D points



triangulation


bundle adjustment

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Algorithm


rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


Image Matching













64

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts











65






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


EduServ 12 (2014)


66





Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts

wwweurosdrnet



Legal Aspects



Geoinformatik


wwweurosdrnet









69









for subsequent use



rt I-4

ndash L

ega

l Asp

ects




70





rt I-4

ndash L

ega

l Asp

ects





Privacy


apply




72

Pa

rt I-4

ndash L

ega

l Asp

ects







growing


aviation background


before end 2020


73

Pa

rt I-4

ndash L

ega

l Asp

ects



Germany








(Permit required)




74

Pa

rt I-4

ndash L

ega

l Asp

ects


75



77



European Regulation

78





framework






Pa

rt I-4

ndash L

ega

l Asp

ects




79

Pa

rt I-4

ndash L

ega

l Asp

ects



3 Categories

80

Open Category


model planes

and UAS

ndash Geofencing

ndash Subcategories

in relation to

potential harm

ndash Exemption for

toys

ndash Control thru

police

Certified Category


UAS gt 25 kg

bull Certification

similar to

manned aviation

bull Pilot licence

(PPL)


Flight Operation

through Certified

Entities

Specific Category

bull Mostly for

commercial

UAS-users


bull Requirements

depend on use

of operation


Flight Operation)


Entitiesldquo

Pa

rt I-4

ndash L

ega

l Asp

ects



81

Pa

rt I-4

ndash L

ega

l Asp

ects



RPAS segments

82








rt I-4

ndash L

ega

l Asp

ects



RPAS segments









years



83

Pa

rt I-4

ndash L

ega

l Asp

ects

wwweurosdrnet








Terminology

17















Terminology

18






(CAP722 CAA UK)








UA

S S

yste

ms


Components of RPAS

19


Ground station

Avionics

Mission-

planning

Energy

supply

Data transfer

Data transfer

Propulsion and


instruments

Offline control

Imaging sensors


Control

airframe

Data


Flight segment


Mis

sio

n C

on

trol

Navigation

- Orientation

- Sensors


rt I-2

ndash S

yste

ms amp

Se

nso

rs


RPAS-Classification

20


Flight Altitude (m)

Endurance (h)

MTOW (kg)




Close Range CR 10-30 3000 2-4 150

Short Range SR 30-70 3000 3-6 200




MALE gt500 14000 24-48 1500


HALE gt2000 20000 24-48 4500-12000




van Blyenburg 2008

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs


Micro and Mini-RPAS

21

Fixed wing


Blimp

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs




22

Fixed wing

UAS UAS Model



Cost Cost + ++ + +





Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



23

bull Hand start


RPAS lt 6 kg


bull Start Catapult

ndash heavy

ndash complex

ndash dangerous

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



24

bull Net



bull Parachute



Pa

rt II

ndash S

yste

ms amp

Se

nso

rs



25

Pa

rt II

ndash S

yste

ms amp

Se

nso

rs + small




- Fish eye lens

+ small


+ external exposure

control



light)


+ Image quality



+ external exposure

control

- heavy (gt 500 g)



RPAS flights

26


05 pixel



compensation (FMC)





windy conditions


latency

119906 =119888 lowast 120596 lowast ∆119905

119862119862119863[micro119898]

Pa

rt II

ndash S

yste

ms amp

Se

nso

rs



RPAS flights

27


speed to keep image



time

Example


c = 9 mm


of 118degsec




Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs


Stabilized mounts

28







Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



29






landing






Quadro copter-Start


rt I-2

ndash S

yste

ms amp

Se

nso

rs



30


their environment



Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



31




navigation



bull Problems


buildings


ndash Expensive

ndash hellip



Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



32









Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



33




ndash Payload 200 g






pilot and Gimbal


Dji Phantom 2

ArduPilot Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



34


RPAS (examples)





Geo referencing




ndash FOV 100deg

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs


RPAS-laser scanning

35






FOV


than 1000 ft




parallel scan lines




RIEGL RiCOPTER

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



36

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



camera

37

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



38

φi

i

Light

source

Observer

North

φr

r

)(

)()(

ii

rriirrii

E

L

BRDF





F

D A A

B

C E G

O

Honkavaara 2014

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs

wwweurosdrnet



Michael Cramer




wwweurosdrnet








Data Acquisition

RPAS Photogrammetry

=




rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts

41





Distance


Base

xlsquo

xlsquolsquo

Accuracy parameters


ndash Base


bull Measurement

accuracy in image

space




quality


sXY

sZ


Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





Distance Z

Base B

xlsquo

xlsquolsquo

sXY

sZ

43

x X y Y

c Z c Z

x X B y Y

c Z c Z

x

c B c BZ

x x p

y yY Z Z

c c

xX Z

c


Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





Distance Z

Base B

xlsquo

xlsquolsquo



Z b x

Y X b x

Zm

B

m

s s

s s s

sXY

sZ

2

Z Z

x Z b Z

Z B

Zm

c

s s

s s s

Accuracy

44


Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



photogrammetry




xlsquo

xlsquolsquo




sXY

sZ



(analog) airborne






projects

45

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





bull Image scale



XYZ b xq ms s

Z b x

Y X b x

Zm

m

Bs s

s s s


46

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts






11 21 31

13 23 33

12 22 32

13 23 33

r X r Y r Zx z

r X r Y r Z

r X r Y r Zy z

r X r Y r Z

0

0

0

X X X

Y Y Y

Z Z Z

0

0

0

x x x

y y y

z z z c

with 11 12 13

31 32 33

r x r y r zX Z

r x r y r z

21 22 23

31 32 33

r x r y r cY Z

r x r y r c


coordinate frames



coordinates





47

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



0

0

0

X X X

Y Y Y

Z Z Z

0

0

0

x x x

y y y

z z z c


11 21 31

13 23 33

12 22 32

13 23 33

r X r Y r Zx z x

r X r Y r Z

r X r Y r Zy z y

r X r Y r Z









with

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


Camera Calibration





49

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Object coordinate

system

camera

P object point

Plsquo image point


cx

cz

cy

0X

X

)( Rp

p



X

Y

Z

0

l l l Cam

Cam X X R p

50

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




Unit cx

cz

cy

X

Y

Z

bzby

bx


0X

X

)( Rp

p

0

bX

GPS

bX

Cam

bX

e



Object coordinate

system

camera

P object point

Plsquo image point


51

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





Keep in mind





0 l l Cab b b

Ca

m


b b

Cam GPS X X

( )b

Cam R

( ) ( )l n

b b R R

52

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




close-range

53

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Standard-AT

GNSS supported AT

few control points

Calibrated cams +

self-calibration

(math models)

GNSSinertial data



FBMLSM)

RPAS

Few control points

Full in-situ camera

calibration

(physical models

GNSS (code)



(SIFT key points)

camera calibration


up of Image Block


block

Product generation

DTMDSM (Dense

Matching) amp Ortho

Transformation into


Process chain

54

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts










image




55

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




56





x1j

x2j

x3j

Xj

P1

P2

P3

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




copy R Fergus 2014

Incremental SfM

58

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Algorithm






(DLT)



60

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


ca

me

ras

points

61


Algorithm







calibration


new 3D points



triangulation


bundle adjustment

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


ca

me

ras

points

62


Algorithm







calibration


new 3D points



triangulation


bundle adjustment

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Algorithm


rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


Image Matching













64

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts











65






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


EduServ 12 (2014)


66





Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts

wwweurosdrnet



Legal Aspects



Geoinformatik


wwweurosdrnet









69









for subsequent use



rt I-4

ndash L

ega

l Asp

ects




70





rt I-4

ndash L

ega

l Asp

ects





Privacy


apply




72

Pa

rt I-4

ndash L

ega

l Asp

ects







growing


aviation background


before end 2020


73

Pa

rt I-4

ndash L

ega

l Asp

ects



Germany








(Permit required)




74

Pa

rt I-4

ndash L

ega

l Asp

ects


75



77



European Regulation

78





framework






Pa

rt I-4

ndash L

ega

l Asp

ects




79

Pa

rt I-4

ndash L

ega

l Asp

ects



3 Categories

80

Open Category


model planes

and UAS

ndash Geofencing

ndash Subcategories

in relation to

potential harm

ndash Exemption for

toys

ndash Control thru

police

Certified Category


UAS gt 25 kg

bull Certification

similar to

manned aviation

bull Pilot licence

(PPL)


Flight Operation

through Certified

Entities

Specific Category

bull Mostly for

commercial

UAS-users


bull Requirements

depend on use

of operation


Flight Operation)


Entitiesldquo

Pa

rt I-4

ndash L

ega

l Asp

ects



81

Pa

rt I-4

ndash L

ega

l Asp

ects



RPAS segments

82








rt I-4

ndash L

ega

l Asp

ects



RPAS segments









years



83

Pa

rt I-4

ndash L

ega

l Asp

ects


Terminology

17















Terminology

18






(CAP722 CAA UK)








UA

S S

yste

ms


Components of RPAS

19


Ground station

Avionics

Mission-

planning

Energy

supply

Data transfer

Data transfer

Propulsion and


instruments

Offline control

Imaging sensors


Control

airframe

Data


Flight segment


Mis

sio

n C

on

trol

Navigation

- Orientation

- Sensors


rt I-2

ndash S

yste

ms amp

Se

nso

rs


RPAS-Classification

20


Flight Altitude (m)

Endurance (h)

MTOW (kg)




Close Range CR 10-30 3000 2-4 150

Short Range SR 30-70 3000 3-6 200




MALE gt500 14000 24-48 1500


HALE gt2000 20000 24-48 4500-12000




van Blyenburg 2008

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs


Micro and Mini-RPAS

21

Fixed wing


Blimp

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs




22

Fixed wing

UAS UAS Model



Cost Cost + ++ + +





Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



23

bull Hand start


RPAS lt 6 kg


bull Start Catapult

ndash heavy

ndash complex

ndash dangerous

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



24

bull Net



bull Parachute



Pa

rt II

ndash S

yste

ms amp

Se

nso

rs



25

Pa

rt II

ndash S

yste

ms amp

Se

nso

rs + small




- Fish eye lens

+ small


+ external exposure

control



light)


+ Image quality



+ external exposure

control

- heavy (gt 500 g)



RPAS flights

26


05 pixel



compensation (FMC)





windy conditions


latency

119906 =119888 lowast 120596 lowast ∆119905

119862119862119863[micro119898]

Pa

rt II

ndash S

yste

ms amp

Se

nso

rs



RPAS flights

27


speed to keep image



time

Example


c = 9 mm


of 118degsec




Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs


Stabilized mounts

28







Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



29






landing






Quadro copter-Start


rt I-2

ndash S

yste

ms amp

Se

nso

rs



30


their environment



Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



31




navigation



bull Problems


buildings


ndash Expensive

ndash hellip



Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



32









Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



33




ndash Payload 200 g






pilot and Gimbal


Dji Phantom 2

ArduPilot Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



34


RPAS (examples)





Geo referencing




ndash FOV 100deg

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs


RPAS-laser scanning

35






FOV


than 1000 ft




parallel scan lines




RIEGL RiCOPTER

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



36

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



camera

37

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



38

φi

i

Light

source

Observer

North

φr

r

)(

)()(

ii

rriirrii

E

L

BRDF





F

D A A

B

C E G

O

Honkavaara 2014

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs

wwweurosdrnet



Michael Cramer




wwweurosdrnet








Data Acquisition

RPAS Photogrammetry

=




rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts

41





Distance


Base

xlsquo

xlsquolsquo

Accuracy parameters


ndash Base


bull Measurement

accuracy in image

space




quality


sXY

sZ


Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





Distance Z

Base B

xlsquo

xlsquolsquo

sXY

sZ

43

x X y Y

c Z c Z

x X B y Y

c Z c Z

x

c B c BZ

x x p

y yY Z Z

c c

xX Z

c


Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





Distance Z

Base B

xlsquo

xlsquolsquo



Z b x

Y X b x

Zm

B

m

s s

s s s

sXY

sZ

2

Z Z

x Z b Z

Z B

Zm

c

s s

s s s

Accuracy

44


Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



photogrammetry




xlsquo

xlsquolsquo




sXY

sZ



(analog) airborne






projects

45

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





bull Image scale



XYZ b xq ms s

Z b x

Y X b x

Zm

m

Bs s

s s s


46

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts






11 21 31

13 23 33

12 22 32

13 23 33

r X r Y r Zx z

r X r Y r Z

r X r Y r Zy z

r X r Y r Z

0

0

0

X X X

Y Y Y

Z Z Z

0

0

0

x x x

y y y

z z z c

with 11 12 13

31 32 33

r x r y r zX Z

r x r y r z

21 22 23

31 32 33

r x r y r cY Z

r x r y r c


coordinate frames



coordinates





47

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



0

0

0

X X X

Y Y Y

Z Z Z

0

0

0

x x x

y y y

z z z c


11 21 31

13 23 33

12 22 32

13 23 33

r X r Y r Zx z x

r X r Y r Z

r X r Y r Zy z y

r X r Y r Z









with

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


Camera Calibration





49

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Object coordinate

system

camera

P object point

Plsquo image point


cx

cz

cy

0X

X

)( Rp

p



X

Y

Z

0

l l l Cam

Cam X X R p

50

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




Unit cx

cz

cy

X

Y

Z

bzby

bx


0X

X

)( Rp

p

0

bX

GPS

bX

Cam

bX

e



Object coordinate

system

camera

P object point

Plsquo image point


51

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





Keep in mind





0 l l Cab b b

Ca

m


b b

Cam GPS X X

( )b

Cam R

( ) ( )l n

b b R R

52

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




close-range

53

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Standard-AT

GNSS supported AT

few control points

Calibrated cams +

self-calibration

(math models)

GNSSinertial data



FBMLSM)

RPAS

Few control points

Full in-situ camera

calibration

(physical models

GNSS (code)



(SIFT key points)

camera calibration


up of Image Block


block

Product generation

DTMDSM (Dense

Matching) amp Ortho

Transformation into


Process chain

54

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts










image




55

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




56





x1j

x2j

x3j

Xj

P1

P2

P3

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




copy R Fergus 2014

Incremental SfM

58

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Algorithm






(DLT)



60

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


ca

me

ras

points

61


Algorithm







calibration


new 3D points



triangulation


bundle adjustment

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


ca

me

ras

points

62


Algorithm







calibration


new 3D points



triangulation


bundle adjustment

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Algorithm


rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


Image Matching













64

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts











65






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


EduServ 12 (2014)


66





Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts

wwweurosdrnet



Legal Aspects



Geoinformatik


wwweurosdrnet









69









for subsequent use



rt I-4

ndash L

ega

l Asp

ects




70





rt I-4

ndash L

ega

l Asp

ects





Privacy


apply




72

Pa

rt I-4

ndash L

ega

l Asp

ects







growing


aviation background


before end 2020


73

Pa

rt I-4

ndash L

ega

l Asp

ects



Germany








(Permit required)




74

Pa

rt I-4

ndash L

ega

l Asp

ects


75



77



European Regulation

78





framework






Pa

rt I-4

ndash L

ega

l Asp

ects




79

Pa

rt I-4

ndash L

ega

l Asp

ects



3 Categories

80

Open Category


model planes

and UAS

ndash Geofencing

ndash Subcategories

in relation to

potential harm

ndash Exemption for

toys

ndash Control thru

police

Certified Category


UAS gt 25 kg

bull Certification

similar to

manned aviation

bull Pilot licence

(PPL)


Flight Operation

through Certified

Entities

Specific Category

bull Mostly for

commercial

UAS-users


bull Requirements

depend on use

of operation


Flight Operation)


Entitiesldquo

Pa

rt I-4

ndash L

ega

l Asp

ects



81

Pa

rt I-4

ndash L

ega

l Asp

ects



RPAS segments

82








rt I-4

ndash L

ega

l Asp

ects



RPAS segments









years



83

Pa

rt I-4

ndash L

ega

l Asp

ects


Terminology

18






(CAP722 CAA UK)








UA

S S

yste

ms


Components of RPAS

19


Ground station

Avionics

Mission-

planning

Energy

supply

Data transfer

Data transfer

Propulsion and


instruments

Offline control

Imaging sensors


Control

airframe

Data


Flight segment


Mis

sio

n C

on

trol

Navigation

- Orientation

- Sensors


rt I-2

ndash S

yste

ms amp

Se

nso

rs


RPAS-Classification

20


Flight Altitude (m)

Endurance (h)

MTOW (kg)




Close Range CR 10-30 3000 2-4 150

Short Range SR 30-70 3000 3-6 200




MALE gt500 14000 24-48 1500


HALE gt2000 20000 24-48 4500-12000




van Blyenburg 2008

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs


Micro and Mini-RPAS

21

Fixed wing


Blimp

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs




22

Fixed wing

UAS UAS Model



Cost Cost + ++ + +





Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



23

bull Hand start


RPAS lt 6 kg


bull Start Catapult

ndash heavy

ndash complex

ndash dangerous

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



24

bull Net



bull Parachute



Pa

rt II

ndash S

yste

ms amp

Se

nso

rs



25

Pa

rt II

ndash S

yste

ms amp

Se

nso

rs + small




- Fish eye lens

+ small


+ external exposure

control



light)


+ Image quality



+ external exposure

control

- heavy (gt 500 g)



RPAS flights

26


05 pixel



compensation (FMC)





windy conditions


latency

119906 =119888 lowast 120596 lowast ∆119905

119862119862119863[micro119898]

Pa

rt II

ndash S

yste

ms amp

Se

nso

rs



RPAS flights

27


speed to keep image



time

Example


c = 9 mm


of 118degsec




Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs


Stabilized mounts

28







Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



29






landing






Quadro copter-Start


rt I-2

ndash S

yste

ms amp

Se

nso

rs



30


their environment



Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



31




navigation



bull Problems


buildings


ndash Expensive

ndash hellip



Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



32









Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



33




ndash Payload 200 g






pilot and Gimbal


Dji Phantom 2

ArduPilot Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



34


RPAS (examples)





Geo referencing




ndash FOV 100deg

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs


RPAS-laser scanning

35






FOV


than 1000 ft




parallel scan lines




RIEGL RiCOPTER

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



36

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



camera

37

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



38

φi

i

Light

source

Observer

North

φr

r

)(

)()(

ii

rriirrii

E

L

BRDF





F

D A A

B

C E G

O

Honkavaara 2014

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs

wwweurosdrnet



Michael Cramer




wwweurosdrnet








Data Acquisition

RPAS Photogrammetry

=




rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts

41





Distance


Base

xlsquo

xlsquolsquo

Accuracy parameters


ndash Base


bull Measurement

accuracy in image

space




quality


sXY

sZ


Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





Distance Z

Base B

xlsquo

xlsquolsquo

sXY

sZ

43

x X y Y

c Z c Z

x X B y Y

c Z c Z

x

c B c BZ

x x p

y yY Z Z

c c

xX Z

c


Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





Distance Z

Base B

xlsquo

xlsquolsquo



Z b x

Y X b x

Zm

B

m

s s

s s s

sXY

sZ

2

Z Z

x Z b Z

Z B

Zm

c

s s

s s s

Accuracy

44


Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



photogrammetry




xlsquo

xlsquolsquo




sXY

sZ



(analog) airborne






projects

45

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





bull Image scale



XYZ b xq ms s

Z b x

Y X b x

Zm

m

Bs s

s s s


46

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts






11 21 31

13 23 33

12 22 32

13 23 33

r X r Y r Zx z

r X r Y r Z

r X r Y r Zy z

r X r Y r Z

0

0

0

X X X

Y Y Y

Z Z Z

0

0

0

x x x

y y y

z z z c

with 11 12 13

31 32 33

r x r y r zX Z

r x r y r z

21 22 23

31 32 33

r x r y r cY Z

r x r y r c


coordinate frames



coordinates





47

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



0

0

0

X X X

Y Y Y

Z Z Z

0

0

0

x x x

y y y

z z z c


11 21 31

13 23 33

12 22 32

13 23 33

r X r Y r Zx z x

r X r Y r Z

r X r Y r Zy z y

r X r Y r Z









with

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


Camera Calibration





49

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Object coordinate

system

camera

P object point

Plsquo image point


cx

cz

cy

0X

X

)( Rp

p



X

Y

Z

0

l l l Cam

Cam X X R p

50

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




Unit cx

cz

cy

X

Y

Z

bzby

bx


0X

X

)( Rp

p

0

bX

GPS

bX

Cam

bX

e



Object coordinate

system

camera

P object point

Plsquo image point


51

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





Keep in mind





0 l l Cab b b

Ca

m


b b

Cam GPS X X

( )b

Cam R

( ) ( )l n

b b R R

52

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




close-range

53

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Standard-AT

GNSS supported AT

few control points

Calibrated cams +

self-calibration

(math models)

GNSSinertial data



FBMLSM)

RPAS

Few control points

Full in-situ camera

calibration

(physical models

GNSS (code)



(SIFT key points)

camera calibration


up of Image Block


block

Product generation

DTMDSM (Dense

Matching) amp Ortho

Transformation into


Process chain

54

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts










image




55

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




56





x1j

x2j

x3j

Xj

P1

P2

P3

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




copy R Fergus 2014

Incremental SfM

58

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Algorithm






(DLT)



60

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


ca

me

ras

points

61


Algorithm







calibration


new 3D points



triangulation


bundle adjustment

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


ca

me

ras

points

62


Algorithm







calibration


new 3D points



triangulation


bundle adjustment

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Algorithm


rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


Image Matching













64

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts











65






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


EduServ 12 (2014)


66





Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts

wwweurosdrnet



Legal Aspects



Geoinformatik


wwweurosdrnet









69









for subsequent use



rt I-4

ndash L

ega

l Asp

ects




70





rt I-4

ndash L

ega

l Asp

ects





Privacy


apply




72

Pa

rt I-4

ndash L

ega

l Asp

ects







growing


aviation background


before end 2020


73

Pa

rt I-4

ndash L

ega

l Asp

ects



Germany








(Permit required)




74

Pa

rt I-4

ndash L

ega

l Asp

ects


75



77



European Regulation

78





framework






Pa

rt I-4

ndash L

ega

l Asp

ects




79

Pa

rt I-4

ndash L

ega

l Asp

ects



3 Categories

80

Open Category


model planes

and UAS

ndash Geofencing

ndash Subcategories

in relation to

potential harm

ndash Exemption for

toys

ndash Control thru

police

Certified Category


UAS gt 25 kg

bull Certification

similar to

manned aviation

bull Pilot licence

(PPL)


Flight Operation

through Certified

Entities

Specific Category

bull Mostly for

commercial

UAS-users


bull Requirements

depend on use

of operation


Flight Operation)


Entitiesldquo

Pa

rt I-4

ndash L

ega

l Asp

ects



81

Pa

rt I-4

ndash L

ega

l Asp

ects



RPAS segments

82








rt I-4

ndash L

ega

l Asp

ects



RPAS segments









years



83

Pa

rt I-4

ndash L

ega

l Asp

ects


Components of RPAS

19


Ground station

Avionics

Mission-

planning

Energy

supply

Data transfer

Data transfer

Propulsion and


instruments

Offline control

Imaging sensors


Control

airframe

Data


Flight segment


Mis

sio

n C

on

trol

Navigation

- Orientation

- Sensors


rt I-2

ndash S

yste

ms amp

Se

nso

rs


RPAS-Classification

20


Flight Altitude (m)

Endurance (h)

MTOW (kg)




Close Range CR 10-30 3000 2-4 150

Short Range SR 30-70 3000 3-6 200




MALE gt500 14000 24-48 1500


HALE gt2000 20000 24-48 4500-12000




van Blyenburg 2008

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs


Micro and Mini-RPAS

21

Fixed wing


Blimp

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs




22

Fixed wing

UAS UAS Model



Cost Cost + ++ + +





Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



23

bull Hand start


RPAS lt 6 kg


bull Start Catapult

ndash heavy

ndash complex

ndash dangerous

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



24

bull Net



bull Parachute



Pa

rt II

ndash S

yste

ms amp

Se

nso

rs



25

Pa

rt II

ndash S

yste

ms amp

Se

nso

rs + small




- Fish eye lens

+ small


+ external exposure

control



light)


+ Image quality



+ external exposure

control

- heavy (gt 500 g)



RPAS flights

26


05 pixel



compensation (FMC)





windy conditions


latency

119906 =119888 lowast 120596 lowast ∆119905

119862119862119863[micro119898]

Pa

rt II

ndash S

yste

ms amp

Se

nso

rs



RPAS flights

27


speed to keep image



time

Example


c = 9 mm


of 118degsec




Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs


Stabilized mounts

28







Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



29






landing






Quadro copter-Start


rt I-2

ndash S

yste

ms amp

Se

nso

rs



30


their environment



Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



31




navigation



bull Problems


buildings


ndash Expensive

ndash hellip



Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



32









Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



33




ndash Payload 200 g






pilot and Gimbal


Dji Phantom 2

ArduPilot Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



34


RPAS (examples)





Geo referencing




ndash FOV 100deg

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs


RPAS-laser scanning

35






FOV


than 1000 ft




parallel scan lines




RIEGL RiCOPTER

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



36

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



camera

37

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



38

φi

i

Light

source

Observer

North

φr

r

)(

)()(

ii

rriirrii

E

L

BRDF





F

D A A

B

C E G

O

Honkavaara 2014

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs

wwweurosdrnet



Michael Cramer




wwweurosdrnet








Data Acquisition

RPAS Photogrammetry

=




rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts

41





Distance


Base

xlsquo

xlsquolsquo

Accuracy parameters


ndash Base


bull Measurement

accuracy in image

space




quality


sXY

sZ


Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





Distance Z

Base B

xlsquo

xlsquolsquo

sXY

sZ

43

x X y Y

c Z c Z

x X B y Y

c Z c Z

x

c B c BZ

x x p

y yY Z Z

c c

xX Z

c


Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





Distance Z

Base B

xlsquo

xlsquolsquo



Z b x

Y X b x

Zm

B

m

s s

s s s

sXY

sZ

2

Z Z

x Z b Z

Z B

Zm

c

s s

s s s

Accuracy

44


Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



photogrammetry




xlsquo

xlsquolsquo




sXY

sZ



(analog) airborne






projects

45

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





bull Image scale



XYZ b xq ms s

Z b x

Y X b x

Zm

m

Bs s

s s s


46

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts






11 21 31

13 23 33

12 22 32

13 23 33

r X r Y r Zx z

r X r Y r Z

r X r Y r Zy z

r X r Y r Z

0

0

0

X X X

Y Y Y

Z Z Z

0

0

0

x x x

y y y

z z z c

with 11 12 13

31 32 33

r x r y r zX Z

r x r y r z

21 22 23

31 32 33

r x r y r cY Z

r x r y r c


coordinate frames



coordinates





47

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



0

0

0

X X X

Y Y Y

Z Z Z

0

0

0

x x x

y y y

z z z c


11 21 31

13 23 33

12 22 32

13 23 33

r X r Y r Zx z x

r X r Y r Z

r X r Y r Zy z y

r X r Y r Z









with

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


Camera Calibration





49

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Object coordinate

system

camera

P object point

Plsquo image point


cx

cz

cy

0X

X

)( Rp

p



X

Y

Z

0

l l l Cam

Cam X X R p

50

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




Unit cx

cz

cy

X

Y

Z

bzby

bx


0X

X

)( Rp

p

0

bX

GPS

bX

Cam

bX

e



Object coordinate

system

camera

P object point

Plsquo image point


51

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





Keep in mind





0 l l Cab b b

Ca

m


b b

Cam GPS X X

( )b

Cam R

( ) ( )l n

b b R R

52

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




close-range

53

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Standard-AT

GNSS supported AT

few control points

Calibrated cams +

self-calibration

(math models)

GNSSinertial data



FBMLSM)

RPAS

Few control points

Full in-situ camera

calibration

(physical models

GNSS (code)



(SIFT key points)

camera calibration


up of Image Block


block

Product generation

DTMDSM (Dense

Matching) amp Ortho

Transformation into


Process chain

54

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts










image




55

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




56





x1j

x2j

x3j

Xj

P1

P2

P3

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




copy R Fergus 2014

Incremental SfM

58

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Algorithm






(DLT)



60

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


ca

me

ras

points

61


Algorithm







calibration


new 3D points



triangulation


bundle adjustment

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


ca

me

ras

points

62


Algorithm







calibration


new 3D points



triangulation


bundle adjustment

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Algorithm


rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


Image Matching













64

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts











65






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


EduServ 12 (2014)


66





Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts

wwweurosdrnet



Legal Aspects



Geoinformatik


wwweurosdrnet









69









for subsequent use



rt I-4

ndash L

ega

l Asp

ects




70





rt I-4

ndash L

ega

l Asp

ects





Privacy


apply




72

Pa

rt I-4

ndash L

ega

l Asp

ects







growing


aviation background


before end 2020


73

Pa

rt I-4

ndash L

ega

l Asp

ects



Germany








(Permit required)




74

Pa

rt I-4

ndash L

ega

l Asp

ects


75



77



European Regulation

78





framework






Pa

rt I-4

ndash L

ega

l Asp

ects




79

Pa

rt I-4

ndash L

ega

l Asp

ects



3 Categories

80

Open Category


model planes

and UAS

ndash Geofencing

ndash Subcategories

in relation to

potential harm

ndash Exemption for

toys

ndash Control thru

police

Certified Category


UAS gt 25 kg

bull Certification

similar to

manned aviation

bull Pilot licence

(PPL)


Flight Operation

through Certified

Entities

Specific Category

bull Mostly for

commercial

UAS-users


bull Requirements

depend on use

of operation


Flight Operation)


Entitiesldquo

Pa

rt I-4

ndash L

ega

l Asp

ects



81

Pa

rt I-4

ndash L

ega

l Asp

ects



RPAS segments

82








rt I-4

ndash L

ega

l Asp

ects



RPAS segments









years



83

Pa

rt I-4

ndash L

ega

l Asp

ects


RPAS-Classification

20


Flight Altitude (m)

Endurance (h)

MTOW (kg)




Close Range CR 10-30 3000 2-4 150

Short Range SR 30-70 3000 3-6 200




MALE gt500 14000 24-48 1500


HALE gt2000 20000 24-48 4500-12000




van Blyenburg 2008

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs


Micro and Mini-RPAS

21

Fixed wing


Blimp

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs




22

Fixed wing

UAS UAS Model



Cost Cost + ++ + +





Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



23

bull Hand start


RPAS lt 6 kg


bull Start Catapult

ndash heavy

ndash complex

ndash dangerous

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



24

bull Net



bull Parachute



Pa

rt II

ndash S

yste

ms amp

Se

nso

rs



25

Pa

rt II

ndash S

yste

ms amp

Se

nso

rs + small




- Fish eye lens

+ small


+ external exposure

control



light)


+ Image quality



+ external exposure

control

- heavy (gt 500 g)



RPAS flights

26


05 pixel



compensation (FMC)





windy conditions


latency

119906 =119888 lowast 120596 lowast ∆119905

119862119862119863[micro119898]

Pa

rt II

ndash S

yste

ms amp

Se

nso

rs



RPAS flights

27


speed to keep image



time

Example


c = 9 mm


of 118degsec




Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs


Stabilized mounts

28







Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



29






landing






Quadro copter-Start


rt I-2

ndash S

yste

ms amp

Se

nso

rs



30


their environment



Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



31




navigation



bull Problems


buildings


ndash Expensive

ndash hellip



Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



32









Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



33




ndash Payload 200 g






pilot and Gimbal


Dji Phantom 2

ArduPilot Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



34


RPAS (examples)





Geo referencing




ndash FOV 100deg

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs


RPAS-laser scanning

35






FOV


than 1000 ft




parallel scan lines




RIEGL RiCOPTER

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



36

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



camera

37

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



38

φi

i

Light

source

Observer

North

φr

r

)(

)()(

ii

rriirrii

E

L

BRDF





F

D A A

B

C E G

O

Honkavaara 2014

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs

wwweurosdrnet



Michael Cramer




wwweurosdrnet








Data Acquisition

RPAS Photogrammetry

=




rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts

41





Distance


Base

xlsquo

xlsquolsquo

Accuracy parameters


ndash Base


bull Measurement

accuracy in image

space




quality


sXY

sZ


Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





Distance Z

Base B

xlsquo

xlsquolsquo

sXY

sZ

43

x X y Y

c Z c Z

x X B y Y

c Z c Z

x

c B c BZ

x x p

y yY Z Z

c c

xX Z

c


Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





Distance Z

Base B

xlsquo

xlsquolsquo



Z b x

Y X b x

Zm

B

m

s s

s s s

sXY

sZ

2

Z Z

x Z b Z

Z B

Zm

c

s s

s s s

Accuracy

44


Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



photogrammetry




xlsquo

xlsquolsquo




sXY

sZ



(analog) airborne






projects

45

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





bull Image scale



XYZ b xq ms s

Z b x

Y X b x

Zm

m

Bs s

s s s


46

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts






11 21 31

13 23 33

12 22 32

13 23 33

r X r Y r Zx z

r X r Y r Z

r X r Y r Zy z

r X r Y r Z

0

0

0

X X X

Y Y Y

Z Z Z

0

0

0

x x x

y y y

z z z c

with 11 12 13

31 32 33

r x r y r zX Z

r x r y r z

21 22 23

31 32 33

r x r y r cY Z

r x r y r c


coordinate frames



coordinates





47

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



0

0

0

X X X

Y Y Y

Z Z Z

0

0

0

x x x

y y y

z z z c


11 21 31

13 23 33

12 22 32

13 23 33

r X r Y r Zx z x

r X r Y r Z

r X r Y r Zy z y

r X r Y r Z









with

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


Camera Calibration





49

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Object coordinate

system

camera

P object point

Plsquo image point


cx

cz

cy

0X

X

)( Rp

p



X

Y

Z

0

l l l Cam

Cam X X R p

50

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




Unit cx

cz

cy

X

Y

Z

bzby

bx


0X

X

)( Rp

p

0

bX

GPS

bX

Cam

bX

e



Object coordinate

system

camera

P object point

Plsquo image point


51

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





Keep in mind





0 l l Cab b b

Ca

m


b b

Cam GPS X X

( )b

Cam R

( ) ( )l n

b b R R

52

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




close-range

53

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Standard-AT

GNSS supported AT

few control points

Calibrated cams +

self-calibration

(math models)

GNSSinertial data



FBMLSM)

RPAS

Few control points

Full in-situ camera

calibration

(physical models

GNSS (code)



(SIFT key points)

camera calibration


up of Image Block


block

Product generation

DTMDSM (Dense

Matching) amp Ortho

Transformation into


Process chain

54

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts










image




55

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




56





x1j

x2j

x3j

Xj

P1

P2

P3

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




copy R Fergus 2014

Incremental SfM

58

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Algorithm






(DLT)



60

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


ca

me

ras

points

61


Algorithm







calibration


new 3D points



triangulation


bundle adjustment

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


ca

me

ras

points

62


Algorithm







calibration


new 3D points



triangulation


bundle adjustment

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Algorithm


rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


Image Matching













64

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts











65






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


EduServ 12 (2014)


66





Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts

wwweurosdrnet



Legal Aspects



Geoinformatik


wwweurosdrnet









69









for subsequent use



rt I-4

ndash L

ega

l Asp

ects




70





rt I-4

ndash L

ega

l Asp

ects





Privacy


apply




72

Pa

rt I-4

ndash L

ega

l Asp

ects







growing


aviation background


before end 2020


73

Pa

rt I-4

ndash L

ega

l Asp

ects



Germany








(Permit required)




74

Pa

rt I-4

ndash L

ega

l Asp

ects


75



77



European Regulation

78





framework






Pa

rt I-4

ndash L

ega

l Asp

ects




79

Pa

rt I-4

ndash L

ega

l Asp

ects



3 Categories

80

Open Category


model planes

and UAS

ndash Geofencing

ndash Subcategories

in relation to

potential harm

ndash Exemption for

toys

ndash Control thru

police

Certified Category


UAS gt 25 kg

bull Certification

similar to

manned aviation

bull Pilot licence

(PPL)


Flight Operation

through Certified

Entities

Specific Category

bull Mostly for

commercial

UAS-users


bull Requirements

depend on use

of operation


Flight Operation)


Entitiesldquo

Pa

rt I-4

ndash L

ega

l Asp

ects



81

Pa

rt I-4

ndash L

ega

l Asp

ects



RPAS segments

82








rt I-4

ndash L

ega

l Asp

ects



RPAS segments









years



83

Pa

rt I-4

ndash L

ega

l Asp

ects


Micro and Mini-RPAS

21

Fixed wing


Blimp

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs




22

Fixed wing

UAS UAS Model



Cost Cost + ++ + +





Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



23

bull Hand start


RPAS lt 6 kg


bull Start Catapult

ndash heavy

ndash complex

ndash dangerous

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



24

bull Net



bull Parachute



Pa

rt II

ndash S

yste

ms amp

Se

nso

rs



25

Pa

rt II

ndash S

yste

ms amp

Se

nso

rs + small




- Fish eye lens

+ small


+ external exposure

control



light)


+ Image quality



+ external exposure

control

- heavy (gt 500 g)



RPAS flights

26


05 pixel



compensation (FMC)





windy conditions


latency

119906 =119888 lowast 120596 lowast ∆119905

119862119862119863[micro119898]

Pa

rt II

ndash S

yste

ms amp

Se

nso

rs



RPAS flights

27


speed to keep image



time

Example


c = 9 mm


of 118degsec




Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs


Stabilized mounts

28







Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



29






landing






Quadro copter-Start


rt I-2

ndash S

yste

ms amp

Se

nso

rs



30


their environment



Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



31




navigation



bull Problems


buildings


ndash Expensive

ndash hellip



Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



32









Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



33




ndash Payload 200 g






pilot and Gimbal


Dji Phantom 2

ArduPilot Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



34


RPAS (examples)





Geo referencing




ndash FOV 100deg

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs


RPAS-laser scanning

35






FOV


than 1000 ft




parallel scan lines




RIEGL RiCOPTER

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



36

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



camera

37

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



38

φi

i

Light

source

Observer

North

φr

r

)(

)()(

ii

rriirrii

E

L

BRDF





F

D A A

B

C E G

O

Honkavaara 2014

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs

wwweurosdrnet



Michael Cramer




wwweurosdrnet








Data Acquisition

RPAS Photogrammetry

=




rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts

41





Distance


Base

xlsquo

xlsquolsquo

Accuracy parameters


ndash Base


bull Measurement

accuracy in image

space




quality


sXY

sZ


Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





Distance Z

Base B

xlsquo

xlsquolsquo

sXY

sZ

43

x X y Y

c Z c Z

x X B y Y

c Z c Z

x

c B c BZ

x x p

y yY Z Z

c c

xX Z

c


Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





Distance Z

Base B

xlsquo

xlsquolsquo



Z b x

Y X b x

Zm

B

m

s s

s s s

sXY

sZ

2

Z Z

x Z b Z

Z B

Zm

c

s s

s s s

Accuracy

44


Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



photogrammetry




xlsquo

xlsquolsquo




sXY

sZ



(analog) airborne






projects

45

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





bull Image scale



XYZ b xq ms s

Z b x

Y X b x

Zm

m

Bs s

s s s


46

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts






11 21 31

13 23 33

12 22 32

13 23 33

r X r Y r Zx z

r X r Y r Z

r X r Y r Zy z

r X r Y r Z

0

0

0

X X X

Y Y Y

Z Z Z

0

0

0

x x x

y y y

z z z c

with 11 12 13

31 32 33

r x r y r zX Z

r x r y r z

21 22 23

31 32 33

r x r y r cY Z

r x r y r c


coordinate frames



coordinates





47

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



0

0

0

X X X

Y Y Y

Z Z Z

0

0

0

x x x

y y y

z z z c


11 21 31

13 23 33

12 22 32

13 23 33

r X r Y r Zx z x

r X r Y r Z

r X r Y r Zy z y

r X r Y r Z









with

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


Camera Calibration





49

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Object coordinate

system

camera

P object point

Plsquo image point


cx

cz

cy

0X

X

)( Rp

p



X

Y

Z

0

l l l Cam

Cam X X R p

50

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




Unit cx

cz

cy

X

Y

Z

bzby

bx


0X

X

)( Rp

p

0

bX

GPS

bX

Cam

bX

e



Object coordinate

system

camera

P object point

Plsquo image point


51

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





Keep in mind





0 l l Cab b b

Ca

m


b b

Cam GPS X X

( )b

Cam R

( ) ( )l n

b b R R

52

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




close-range

53

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Standard-AT

GNSS supported AT

few control points

Calibrated cams +

self-calibration

(math models)

GNSSinertial data



FBMLSM)

RPAS

Few control points

Full in-situ camera

calibration

(physical models

GNSS (code)



(SIFT key points)

camera calibration


up of Image Block


block

Product generation

DTMDSM (Dense

Matching) amp Ortho

Transformation into


Process chain

54

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts










image




55

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




56





x1j

x2j

x3j

Xj

P1

P2

P3

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




copy R Fergus 2014

Incremental SfM

58

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Algorithm






(DLT)



60

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


ca

me

ras

points

61


Algorithm







calibration


new 3D points



triangulation


bundle adjustment

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


ca

me

ras

points

62


Algorithm







calibration


new 3D points



triangulation


bundle adjustment

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Algorithm


rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


Image Matching













64

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts











65






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


EduServ 12 (2014)


66





Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts

wwweurosdrnet



Legal Aspects



Geoinformatik


wwweurosdrnet









69









for subsequent use



rt I-4

ndash L

ega

l Asp

ects




70





rt I-4

ndash L

ega

l Asp

ects





Privacy


apply




72

Pa

rt I-4

ndash L

ega

l Asp

ects







growing


aviation background


before end 2020


73

Pa

rt I-4

ndash L

ega

l Asp

ects



Germany








(Permit required)




74

Pa

rt I-4

ndash L

ega

l Asp

ects


75



77



European Regulation

78





framework






Pa

rt I-4

ndash L

ega

l Asp

ects




79

Pa

rt I-4

ndash L

ega

l Asp

ects



3 Categories

80

Open Category


model planes

and UAS

ndash Geofencing

ndash Subcategories

in relation to

potential harm

ndash Exemption for

toys

ndash Control thru

police

Certified Category


UAS gt 25 kg

bull Certification

similar to

manned aviation

bull Pilot licence

(PPL)


Flight Operation

through Certified

Entities

Specific Category

bull Mostly for

commercial

UAS-users


bull Requirements

depend on use

of operation


Flight Operation)


Entitiesldquo

Pa

rt I-4

ndash L

ega

l Asp

ects



81

Pa

rt I-4

ndash L

ega

l Asp

ects



RPAS segments

82








rt I-4

ndash L

ega

l Asp

ects



RPAS segments









years



83

Pa

rt I-4

ndash L

ega

l Asp

ects




22

Fixed wing

UAS UAS Model



Cost Cost + ++ + +





Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



23

bull Hand start


RPAS lt 6 kg


bull Start Catapult

ndash heavy

ndash complex

ndash dangerous

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



24

bull Net



bull Parachute



Pa

rt II

ndash S

yste

ms amp

Se

nso

rs



25

Pa

rt II

ndash S

yste

ms amp

Se

nso

rs + small




- Fish eye lens

+ small


+ external exposure

control



light)


+ Image quality



+ external exposure

control

- heavy (gt 500 g)



RPAS flights

26


05 pixel



compensation (FMC)





windy conditions


latency

119906 =119888 lowast 120596 lowast ∆119905

119862119862119863[micro119898]

Pa

rt II

ndash S

yste

ms amp

Se

nso

rs



RPAS flights

27


speed to keep image



time

Example


c = 9 mm


of 118degsec




Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs


Stabilized mounts

28







Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



29






landing






Quadro copter-Start


rt I-2

ndash S

yste

ms amp

Se

nso

rs



30


their environment



Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



31




navigation



bull Problems


buildings


ndash Expensive

ndash hellip



Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



32









Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



33




ndash Payload 200 g






pilot and Gimbal


Dji Phantom 2

ArduPilot Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



34


RPAS (examples)





Geo referencing




ndash FOV 100deg

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs


RPAS-laser scanning

35






FOV


than 1000 ft




parallel scan lines




RIEGL RiCOPTER

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



36

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



camera

37

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



38

φi

i

Light

source

Observer

North

φr

r

)(

)()(

ii

rriirrii

E

L

BRDF





F

D A A

B

C E G

O

Honkavaara 2014

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs

wwweurosdrnet



Michael Cramer




wwweurosdrnet








Data Acquisition

RPAS Photogrammetry

=




rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts

41





Distance


Base

xlsquo

xlsquolsquo

Accuracy parameters


ndash Base


bull Measurement

accuracy in image

space




quality


sXY

sZ


Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





Distance Z

Base B

xlsquo

xlsquolsquo

sXY

sZ

43

x X y Y

c Z c Z

x X B y Y

c Z c Z

x

c B c BZ

x x p

y yY Z Z

c c

xX Z

c


Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





Distance Z

Base B

xlsquo

xlsquolsquo



Z b x

Y X b x

Zm

B

m

s s

s s s

sXY

sZ

2

Z Z

x Z b Z

Z B

Zm

c

s s

s s s

Accuracy

44


Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



photogrammetry




xlsquo

xlsquolsquo




sXY

sZ



(analog) airborne






projects

45

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





bull Image scale



XYZ b xq ms s

Z b x

Y X b x

Zm

m

Bs s

s s s


46

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts






11 21 31

13 23 33

12 22 32

13 23 33

r X r Y r Zx z

r X r Y r Z

r X r Y r Zy z

r X r Y r Z

0

0

0

X X X

Y Y Y

Z Z Z

0

0

0

x x x

y y y

z z z c

with 11 12 13

31 32 33

r x r y r zX Z

r x r y r z

21 22 23

31 32 33

r x r y r cY Z

r x r y r c


coordinate frames



coordinates





47

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



0

0

0

X X X

Y Y Y

Z Z Z

0

0

0

x x x

y y y

z z z c


11 21 31

13 23 33

12 22 32

13 23 33

r X r Y r Zx z x

r X r Y r Z

r X r Y r Zy z y

r X r Y r Z









with

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


Camera Calibration





49

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Object coordinate

system

camera

P object point

Plsquo image point


cx

cz

cy

0X

X

)( Rp

p



X

Y

Z

0

l l l Cam

Cam X X R p

50

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




Unit cx

cz

cy

X

Y

Z

bzby

bx


0X

X

)( Rp

p

0

bX

GPS

bX

Cam

bX

e



Object coordinate

system

camera

P object point

Plsquo image point


51

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





Keep in mind





0 l l Cab b b

Ca

m


b b

Cam GPS X X

( )b

Cam R

( ) ( )l n

b b R R

52

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




close-range

53

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Standard-AT

GNSS supported AT

few control points

Calibrated cams +

self-calibration

(math models)

GNSSinertial data



FBMLSM)

RPAS

Few control points

Full in-situ camera

calibration

(physical models

GNSS (code)



(SIFT key points)

camera calibration


up of Image Block


block

Product generation

DTMDSM (Dense

Matching) amp Ortho

Transformation into


Process chain

54

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts










image




55

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




56





x1j

x2j

x3j

Xj

P1

P2

P3

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




copy R Fergus 2014

Incremental SfM

58

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Algorithm






(DLT)



60

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


ca

me

ras

points

61


Algorithm







calibration


new 3D points



triangulation


bundle adjustment

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


ca

me

ras

points

62


Algorithm







calibration


new 3D points



triangulation


bundle adjustment

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Algorithm


rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


Image Matching













64

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts











65






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


EduServ 12 (2014)


66





Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts

wwweurosdrnet



Legal Aspects



Geoinformatik


wwweurosdrnet









69









for subsequent use



rt I-4

ndash L

ega

l Asp

ects




70





rt I-4

ndash L

ega

l Asp

ects





Privacy


apply




72

Pa

rt I-4

ndash L

ega

l Asp

ects







growing


aviation background


before end 2020


73

Pa

rt I-4

ndash L

ega

l Asp

ects



Germany








(Permit required)




74

Pa

rt I-4

ndash L

ega

l Asp

ects


75



77



European Regulation

78





framework






Pa

rt I-4

ndash L

ega

l Asp

ects




79

Pa

rt I-4

ndash L

ega

l Asp

ects



3 Categories

80

Open Category


model planes

and UAS

ndash Geofencing

ndash Subcategories

in relation to

potential harm

ndash Exemption for

toys

ndash Control thru

police

Certified Category


UAS gt 25 kg

bull Certification

similar to

manned aviation

bull Pilot licence

(PPL)


Flight Operation

through Certified

Entities

Specific Category

bull Mostly for

commercial

UAS-users


bull Requirements

depend on use

of operation


Flight Operation)


Entitiesldquo

Pa

rt I-4

ndash L

ega

l Asp

ects



81

Pa

rt I-4

ndash L

ega

l Asp

ects



RPAS segments

82








rt I-4

ndash L

ega

l Asp

ects



RPAS segments









years



83

Pa

rt I-4

ndash L

ega

l Asp

ects



23

bull Hand start


RPAS lt 6 kg


bull Start Catapult

ndash heavy

ndash complex

ndash dangerous

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



24

bull Net



bull Parachute



Pa

rt II

ndash S

yste

ms amp

Se

nso

rs



25

Pa

rt II

ndash S

yste

ms amp

Se

nso

rs + small




- Fish eye lens

+ small


+ external exposure

control



light)


+ Image quality



+ external exposure

control

- heavy (gt 500 g)



RPAS flights

26


05 pixel



compensation (FMC)





windy conditions


latency

119906 =119888 lowast 120596 lowast ∆119905

119862119862119863[micro119898]

Pa

rt II

ndash S

yste

ms amp

Se

nso

rs



RPAS flights

27


speed to keep image



time

Example


c = 9 mm


of 118degsec




Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs


Stabilized mounts

28







Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



29






landing






Quadro copter-Start


rt I-2

ndash S

yste

ms amp

Se

nso

rs



30


their environment



Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



31




navigation



bull Problems


buildings


ndash Expensive

ndash hellip



Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



32









Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



33




ndash Payload 200 g






pilot and Gimbal


Dji Phantom 2

ArduPilot Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



34


RPAS (examples)





Geo referencing




ndash FOV 100deg

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs


RPAS-laser scanning

35






FOV


than 1000 ft




parallel scan lines




RIEGL RiCOPTER

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



36

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



camera

37

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



38

φi

i

Light

source

Observer

North

φr

r

)(

)()(

ii

rriirrii

E

L

BRDF





F

D A A

B

C E G

O

Honkavaara 2014

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs

wwweurosdrnet



Michael Cramer




wwweurosdrnet








Data Acquisition

RPAS Photogrammetry

=




rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts

41





Distance


Base

xlsquo

xlsquolsquo

Accuracy parameters


ndash Base


bull Measurement

accuracy in image

space




quality


sXY

sZ


Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





Distance Z

Base B

xlsquo

xlsquolsquo

sXY

sZ

43

x X y Y

c Z c Z

x X B y Y

c Z c Z

x

c B c BZ

x x p

y yY Z Z

c c

xX Z

c


Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





Distance Z

Base B

xlsquo

xlsquolsquo



Z b x

Y X b x

Zm

B

m

s s

s s s

sXY

sZ

2

Z Z

x Z b Z

Z B

Zm

c

s s

s s s

Accuracy

44


Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



photogrammetry




xlsquo

xlsquolsquo




sXY

sZ



(analog) airborne






projects

45

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





bull Image scale



XYZ b xq ms s

Z b x

Y X b x

Zm

m

Bs s

s s s


46

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts






11 21 31

13 23 33

12 22 32

13 23 33

r X r Y r Zx z

r X r Y r Z

r X r Y r Zy z

r X r Y r Z

0

0

0

X X X

Y Y Y

Z Z Z

0

0

0

x x x

y y y

z z z c

with 11 12 13

31 32 33

r x r y r zX Z

r x r y r z

21 22 23

31 32 33

r x r y r cY Z

r x r y r c


coordinate frames



coordinates





47

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



0

0

0

X X X

Y Y Y

Z Z Z

0

0

0

x x x

y y y

z z z c


11 21 31

13 23 33

12 22 32

13 23 33

r X r Y r Zx z x

r X r Y r Z

r X r Y r Zy z y

r X r Y r Z









with

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


Camera Calibration





49

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Object coordinate

system

camera

P object point

Plsquo image point


cx

cz

cy

0X

X

)( Rp

p



X

Y

Z

0

l l l Cam

Cam X X R p

50

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




Unit cx

cz

cy

X

Y

Z

bzby

bx


0X

X

)( Rp

p

0

bX

GPS

bX

Cam

bX

e



Object coordinate

system

camera

P object point

Plsquo image point


51

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





Keep in mind





0 l l Cab b b

Ca

m


b b

Cam GPS X X

( )b

Cam R

( ) ( )l n

b b R R

52

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




close-range

53

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Standard-AT

GNSS supported AT

few control points

Calibrated cams +

self-calibration

(math models)

GNSSinertial data



FBMLSM)

RPAS

Few control points

Full in-situ camera

calibration

(physical models

GNSS (code)



(SIFT key points)

camera calibration


up of Image Block


block

Product generation

DTMDSM (Dense

Matching) amp Ortho

Transformation into


Process chain

54

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts










image




55

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




56





x1j

x2j

x3j

Xj

P1

P2

P3

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




copy R Fergus 2014

Incremental SfM

58

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Algorithm






(DLT)



60

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


ca

me

ras

points

61


Algorithm







calibration


new 3D points



triangulation


bundle adjustment

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


ca

me

ras

points

62


Algorithm







calibration


new 3D points



triangulation


bundle adjustment

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Algorithm


rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


Image Matching













64

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts











65






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


EduServ 12 (2014)


66





Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts

wwweurosdrnet



Legal Aspects



Geoinformatik


wwweurosdrnet









69









for subsequent use



rt I-4

ndash L

ega

l Asp

ects




70





rt I-4

ndash L

ega

l Asp

ects





Privacy


apply




72

Pa

rt I-4

ndash L

ega

l Asp

ects







growing


aviation background


before end 2020


73

Pa

rt I-4

ndash L

ega

l Asp

ects



Germany








(Permit required)




74

Pa

rt I-4

ndash L

ega

l Asp

ects


75



77



European Regulation

78





framework






Pa

rt I-4

ndash L

ega

l Asp

ects




79

Pa

rt I-4

ndash L

ega

l Asp

ects



3 Categories

80

Open Category


model planes

and UAS

ndash Geofencing

ndash Subcategories

in relation to

potential harm

ndash Exemption for

toys

ndash Control thru

police

Certified Category


UAS gt 25 kg

bull Certification

similar to

manned aviation

bull Pilot licence

(PPL)


Flight Operation

through Certified

Entities

Specific Category

bull Mostly for

commercial

UAS-users


bull Requirements

depend on use

of operation


Flight Operation)


Entitiesldquo

Pa

rt I-4

ndash L

ega

l Asp

ects



81

Pa

rt I-4

ndash L

ega

l Asp

ects



RPAS segments

82








rt I-4

ndash L

ega

l Asp

ects



RPAS segments









years



83

Pa

rt I-4

ndash L

ega

l Asp

ects



24

bull Net



bull Parachute



Pa

rt II

ndash S

yste

ms amp

Se

nso

rs



25

Pa

rt II

ndash S

yste

ms amp

Se

nso

rs + small




- Fish eye lens

+ small


+ external exposure

control



light)


+ Image quality



+ external exposure

control

- heavy (gt 500 g)



RPAS flights

26


05 pixel



compensation (FMC)





windy conditions


latency

119906 =119888 lowast 120596 lowast ∆119905

119862119862119863[micro119898]

Pa

rt II

ndash S

yste

ms amp

Se

nso

rs



RPAS flights

27


speed to keep image



time

Example


c = 9 mm


of 118degsec




Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs


Stabilized mounts

28







Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



29






landing






Quadro copter-Start


rt I-2

ndash S

yste

ms amp

Se

nso

rs



30


their environment



Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



31




navigation



bull Problems


buildings


ndash Expensive

ndash hellip



Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



32









Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



33




ndash Payload 200 g






pilot and Gimbal


Dji Phantom 2

ArduPilot Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



34


RPAS (examples)





Geo referencing




ndash FOV 100deg

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs


RPAS-laser scanning

35






FOV


than 1000 ft




parallel scan lines




RIEGL RiCOPTER

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



36

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



camera

37

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



38

φi

i

Light

source

Observer

North

φr

r

)(

)()(

ii

rriirrii

E

L

BRDF





F

D A A

B

C E G

O

Honkavaara 2014

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs

wwweurosdrnet



Michael Cramer




wwweurosdrnet








Data Acquisition

RPAS Photogrammetry

=




rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts

41





Distance


Base

xlsquo

xlsquolsquo

Accuracy parameters


ndash Base


bull Measurement

accuracy in image

space




quality


sXY

sZ


Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





Distance Z

Base B

xlsquo

xlsquolsquo

sXY

sZ

43

x X y Y

c Z c Z

x X B y Y

c Z c Z

x

c B c BZ

x x p

y yY Z Z

c c

xX Z

c


Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





Distance Z

Base B

xlsquo

xlsquolsquo



Z b x

Y X b x

Zm

B

m

s s

s s s

sXY

sZ

2

Z Z

x Z b Z

Z B

Zm

c

s s

s s s

Accuracy

44


Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



photogrammetry




xlsquo

xlsquolsquo




sXY

sZ



(analog) airborne






projects

45

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





bull Image scale



XYZ b xq ms s

Z b x

Y X b x

Zm

m

Bs s

s s s


46

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts






11 21 31

13 23 33

12 22 32

13 23 33

r X r Y r Zx z

r X r Y r Z

r X r Y r Zy z

r X r Y r Z

0

0

0

X X X

Y Y Y

Z Z Z

0

0

0

x x x

y y y

z z z c

with 11 12 13

31 32 33

r x r y r zX Z

r x r y r z

21 22 23

31 32 33

r x r y r cY Z

r x r y r c


coordinate frames



coordinates





47

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



0

0

0

X X X

Y Y Y

Z Z Z

0

0

0

x x x

y y y

z z z c


11 21 31

13 23 33

12 22 32

13 23 33

r X r Y r Zx z x

r X r Y r Z

r X r Y r Zy z y

r X r Y r Z









with

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


Camera Calibration





49

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Object coordinate

system

camera

P object point

Plsquo image point


cx

cz

cy

0X

X

)( Rp

p



X

Y

Z

0

l l l Cam

Cam X X R p

50

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




Unit cx

cz

cy

X

Y

Z

bzby

bx


0X

X

)( Rp

p

0

bX

GPS

bX

Cam

bX

e



Object coordinate

system

camera

P object point

Plsquo image point


51

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





Keep in mind





0 l l Cab b b

Ca

m


b b

Cam GPS X X

( )b

Cam R

( ) ( )l n

b b R R

52

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




close-range

53

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Standard-AT

GNSS supported AT

few control points

Calibrated cams +

self-calibration

(math models)

GNSSinertial data



FBMLSM)

RPAS

Few control points

Full in-situ camera

calibration

(physical models

GNSS (code)



(SIFT key points)

camera calibration


up of Image Block


block

Product generation

DTMDSM (Dense

Matching) amp Ortho

Transformation into


Process chain

54

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts










image




55

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




56





x1j

x2j

x3j

Xj

P1

P2

P3

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




copy R Fergus 2014

Incremental SfM

58

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Algorithm






(DLT)



60

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


ca

me

ras

points

61


Algorithm







calibration


new 3D points



triangulation


bundle adjustment

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


ca

me

ras

points

62


Algorithm







calibration


new 3D points



triangulation


bundle adjustment

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Algorithm


rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


Image Matching













64

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts











65






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


EduServ 12 (2014)


66





Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts

wwweurosdrnet



Legal Aspects



Geoinformatik


wwweurosdrnet









69









for subsequent use



rt I-4

ndash L

ega

l Asp

ects




70





rt I-4

ndash L

ega

l Asp

ects





Privacy


apply




72

Pa

rt I-4

ndash L

ega

l Asp

ects







growing


aviation background


before end 2020


73

Pa

rt I-4

ndash L

ega

l Asp

ects



Germany








(Permit required)




74

Pa

rt I-4

ndash L

ega

l Asp

ects


75



77



European Regulation

78





framework






Pa

rt I-4

ndash L

ega

l Asp

ects




79

Pa

rt I-4

ndash L

ega

l Asp

ects



3 Categories

80

Open Category


model planes

and UAS

ndash Geofencing

ndash Subcategories

in relation to

potential harm

ndash Exemption for

toys

ndash Control thru

police

Certified Category


UAS gt 25 kg

bull Certification

similar to

manned aviation

bull Pilot licence

(PPL)


Flight Operation

through Certified

Entities

Specific Category

bull Mostly for

commercial

UAS-users


bull Requirements

depend on use

of operation


Flight Operation)


Entitiesldquo

Pa

rt I-4

ndash L

ega

l Asp

ects



81

Pa

rt I-4

ndash L

ega

l Asp

ects



RPAS segments

82








rt I-4

ndash L

ega

l Asp

ects



RPAS segments









years



83

Pa

rt I-4

ndash L

ega

l Asp

ects



25

Pa

rt II

ndash S

yste

ms amp

Se

nso

rs + small




- Fish eye lens

+ small


+ external exposure

control



light)


+ Image quality



+ external exposure

control

- heavy (gt 500 g)



RPAS flights

26


05 pixel



compensation (FMC)





windy conditions


latency

119906 =119888 lowast 120596 lowast ∆119905

119862119862119863[micro119898]

Pa

rt II

ndash S

yste

ms amp

Se

nso

rs



RPAS flights

27


speed to keep image



time

Example


c = 9 mm


of 118degsec




Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs


Stabilized mounts

28







Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



29






landing






Quadro copter-Start


rt I-2

ndash S

yste

ms amp

Se

nso

rs



30


their environment



Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



31




navigation



bull Problems


buildings


ndash Expensive

ndash hellip



Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



32









Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



33




ndash Payload 200 g






pilot and Gimbal


Dji Phantom 2

ArduPilot Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



34


RPAS (examples)





Geo referencing




ndash FOV 100deg

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs


RPAS-laser scanning

35






FOV


than 1000 ft




parallel scan lines




RIEGL RiCOPTER

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



36

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



camera

37

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



38

φi

i

Light

source

Observer

North

φr

r

)(

)()(

ii

rriirrii

E

L

BRDF





F

D A A

B

C E G

O

Honkavaara 2014

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs

wwweurosdrnet



Michael Cramer




wwweurosdrnet








Data Acquisition

RPAS Photogrammetry

=




rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts

41





Distance


Base

xlsquo

xlsquolsquo

Accuracy parameters


ndash Base


bull Measurement

accuracy in image

space




quality


sXY

sZ


Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





Distance Z

Base B

xlsquo

xlsquolsquo

sXY

sZ

43

x X y Y

c Z c Z

x X B y Y

c Z c Z

x

c B c BZ

x x p

y yY Z Z

c c

xX Z

c


Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





Distance Z

Base B

xlsquo

xlsquolsquo



Z b x

Y X b x

Zm

B

m

s s

s s s

sXY

sZ

2

Z Z

x Z b Z

Z B

Zm

c

s s

s s s

Accuracy

44


Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



photogrammetry




xlsquo

xlsquolsquo




sXY

sZ



(analog) airborne






projects

45

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





bull Image scale



XYZ b xq ms s

Z b x

Y X b x

Zm

m

Bs s

s s s


46

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts






11 21 31

13 23 33

12 22 32

13 23 33

r X r Y r Zx z

r X r Y r Z

r X r Y r Zy z

r X r Y r Z

0

0

0

X X X

Y Y Y

Z Z Z

0

0

0

x x x

y y y

z z z c

with 11 12 13

31 32 33

r x r y r zX Z

r x r y r z

21 22 23

31 32 33

r x r y r cY Z

r x r y r c


coordinate frames



coordinates





47

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



0

0

0

X X X

Y Y Y

Z Z Z

0

0

0

x x x

y y y

z z z c


11 21 31

13 23 33

12 22 32

13 23 33

r X r Y r Zx z x

r X r Y r Z

r X r Y r Zy z y

r X r Y r Z









with

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


Camera Calibration





49

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Object coordinate

system

camera

P object point

Plsquo image point


cx

cz

cy

0X

X

)( Rp

p



X

Y

Z

0

l l l Cam

Cam X X R p

50

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




Unit cx

cz

cy

X

Y

Z

bzby

bx


0X

X

)( Rp

p

0

bX

GPS

bX

Cam

bX

e



Object coordinate

system

camera

P object point

Plsquo image point


51

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





Keep in mind





0 l l Cab b b

Ca

m


b b

Cam GPS X X

( )b

Cam R

( ) ( )l n

b b R R

52

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




close-range

53

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Standard-AT

GNSS supported AT

few control points

Calibrated cams +

self-calibration

(math models)

GNSSinertial data



FBMLSM)

RPAS

Few control points

Full in-situ camera

calibration

(physical models

GNSS (code)



(SIFT key points)

camera calibration


up of Image Block


block

Product generation

DTMDSM (Dense

Matching) amp Ortho

Transformation into


Process chain

54

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts










image




55

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




56





x1j

x2j

x3j

Xj

P1

P2

P3

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




copy R Fergus 2014

Incremental SfM

58

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Algorithm






(DLT)



60

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


ca

me

ras

points

61


Algorithm







calibration


new 3D points



triangulation


bundle adjustment

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


ca

me

ras

points

62


Algorithm







calibration


new 3D points



triangulation


bundle adjustment

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Algorithm


rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


Image Matching













64

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts











65






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


EduServ 12 (2014)


66





Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts

wwweurosdrnet



Legal Aspects



Geoinformatik


wwweurosdrnet









69









for subsequent use



rt I-4

ndash L

ega

l Asp

ects




70





rt I-4

ndash L

ega

l Asp

ects





Privacy


apply




72

Pa

rt I-4

ndash L

ega

l Asp

ects







growing


aviation background


before end 2020


73

Pa

rt I-4

ndash L

ega

l Asp

ects



Germany








(Permit required)




74

Pa

rt I-4

ndash L

ega

l Asp

ects


75



77



European Regulation

78





framework






Pa

rt I-4

ndash L

ega

l Asp

ects




79

Pa

rt I-4

ndash L

ega

l Asp

ects



3 Categories

80

Open Category


model planes

and UAS

ndash Geofencing

ndash Subcategories

in relation to

potential harm

ndash Exemption for

toys

ndash Control thru

police

Certified Category


UAS gt 25 kg

bull Certification

similar to

manned aviation

bull Pilot licence

(PPL)


Flight Operation

through Certified

Entities

Specific Category

bull Mostly for

commercial

UAS-users


bull Requirements

depend on use

of operation


Flight Operation)


Entitiesldquo

Pa

rt I-4

ndash L

ega

l Asp

ects



81

Pa

rt I-4

ndash L

ega

l Asp

ects



RPAS segments

82








rt I-4

ndash L

ega

l Asp

ects



RPAS segments









years



83

Pa

rt I-4

ndash L

ega

l Asp

ects



RPAS flights

26


05 pixel



compensation (FMC)





windy conditions


latency

119906 =119888 lowast 120596 lowast ∆119905

119862119862119863[micro119898]

Pa

rt II

ndash S

yste

ms amp

Se

nso

rs



RPAS flights

27


speed to keep image



time

Example


c = 9 mm


of 118degsec




Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs


Stabilized mounts

28







Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



29






landing






Quadro copter-Start


rt I-2

ndash S

yste

ms amp

Se

nso

rs



30


their environment



Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



31




navigation



bull Problems


buildings


ndash Expensive

ndash hellip



Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



32









Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



33




ndash Payload 200 g






pilot and Gimbal


Dji Phantom 2

ArduPilot Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



34


RPAS (examples)





Geo referencing




ndash FOV 100deg

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs


RPAS-laser scanning

35






FOV


than 1000 ft




parallel scan lines




RIEGL RiCOPTER

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



36

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



camera

37

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



38

φi

i

Light

source

Observer

North

φr

r

)(

)()(

ii

rriirrii

E

L

BRDF





F

D A A

B

C E G

O

Honkavaara 2014

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs

wwweurosdrnet



Michael Cramer




wwweurosdrnet








Data Acquisition

RPAS Photogrammetry

=




rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts

41





Distance


Base

xlsquo

xlsquolsquo

Accuracy parameters


ndash Base


bull Measurement

accuracy in image

space




quality


sXY

sZ


Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





Distance Z

Base B

xlsquo

xlsquolsquo

sXY

sZ

43

x X y Y

c Z c Z

x X B y Y

c Z c Z

x

c B c BZ

x x p

y yY Z Z

c c

xX Z

c


Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





Distance Z

Base B

xlsquo

xlsquolsquo



Z b x

Y X b x

Zm

B

m

s s

s s s

sXY

sZ

2

Z Z

x Z b Z

Z B

Zm

c

s s

s s s

Accuracy

44


Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



photogrammetry




xlsquo

xlsquolsquo




sXY

sZ



(analog) airborne






projects

45

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





bull Image scale



XYZ b xq ms s

Z b x

Y X b x

Zm

m

Bs s

s s s


46

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts






11 21 31

13 23 33

12 22 32

13 23 33

r X r Y r Zx z

r X r Y r Z

r X r Y r Zy z

r X r Y r Z

0

0

0

X X X

Y Y Y

Z Z Z

0

0

0

x x x

y y y

z z z c

with 11 12 13

31 32 33

r x r y r zX Z

r x r y r z

21 22 23

31 32 33

r x r y r cY Z

r x r y r c


coordinate frames



coordinates





47

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



0

0

0

X X X

Y Y Y

Z Z Z

0

0

0

x x x

y y y

z z z c


11 21 31

13 23 33

12 22 32

13 23 33

r X r Y r Zx z x

r X r Y r Z

r X r Y r Zy z y

r X r Y r Z









with

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


Camera Calibration





49

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Object coordinate

system

camera

P object point

Plsquo image point


cx

cz

cy

0X

X

)( Rp

p



X

Y

Z

0

l l l Cam

Cam X X R p

50

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




Unit cx

cz

cy

X

Y

Z

bzby

bx


0X

X

)( Rp

p

0

bX

GPS

bX

Cam

bX

e



Object coordinate

system

camera

P object point

Plsquo image point


51

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





Keep in mind





0 l l Cab b b

Ca

m


b b

Cam GPS X X

( )b

Cam R

( ) ( )l n

b b R R

52

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




close-range

53

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Standard-AT

GNSS supported AT

few control points

Calibrated cams +

self-calibration

(math models)

GNSSinertial data



FBMLSM)

RPAS

Few control points

Full in-situ camera

calibration

(physical models

GNSS (code)



(SIFT key points)

camera calibration


up of Image Block


block

Product generation

DTMDSM (Dense

Matching) amp Ortho

Transformation into


Process chain

54

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts










image




55

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




56





x1j

x2j

x3j

Xj

P1

P2

P3

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




copy R Fergus 2014

Incremental SfM

58

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Algorithm






(DLT)



60

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


ca

me

ras

points

61


Algorithm







calibration


new 3D points



triangulation


bundle adjustment

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


ca

me

ras

points

62


Algorithm







calibration


new 3D points



triangulation


bundle adjustment

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Algorithm


rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


Image Matching













64

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts











65






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


EduServ 12 (2014)


66





Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts

wwweurosdrnet



Legal Aspects



Geoinformatik


wwweurosdrnet









69









for subsequent use



rt I-4

ndash L

ega

l Asp

ects




70





rt I-4

ndash L

ega

l Asp

ects





Privacy


apply




72

Pa

rt I-4

ndash L

ega

l Asp

ects







growing


aviation background


before end 2020


73

Pa

rt I-4

ndash L

ega

l Asp

ects



Germany








(Permit required)




74

Pa

rt I-4

ndash L

ega

l Asp

ects


75



77



European Regulation

78





framework






Pa

rt I-4

ndash L

ega

l Asp

ects




79

Pa

rt I-4

ndash L

ega

l Asp

ects



3 Categories

80

Open Category


model planes

and UAS

ndash Geofencing

ndash Subcategories

in relation to

potential harm

ndash Exemption for

toys

ndash Control thru

police

Certified Category


UAS gt 25 kg

bull Certification

similar to

manned aviation

bull Pilot licence

(PPL)


Flight Operation

through Certified

Entities

Specific Category

bull Mostly for

commercial

UAS-users


bull Requirements

depend on use

of operation


Flight Operation)


Entitiesldquo

Pa

rt I-4

ndash L

ega

l Asp

ects



81

Pa

rt I-4

ndash L

ega

l Asp

ects



RPAS segments

82








rt I-4

ndash L

ega

l Asp

ects



RPAS segments









years



83

Pa

rt I-4

ndash L

ega

l Asp

ects



RPAS flights

27


speed to keep image



time

Example


c = 9 mm


of 118degsec




Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs


Stabilized mounts

28







Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



29






landing






Quadro copter-Start


rt I-2

ndash S

yste

ms amp

Se

nso

rs



30


their environment



Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



31




navigation



bull Problems


buildings


ndash Expensive

ndash hellip



Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



32









Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



33




ndash Payload 200 g






pilot and Gimbal


Dji Phantom 2

ArduPilot Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



34


RPAS (examples)





Geo referencing




ndash FOV 100deg

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs


RPAS-laser scanning

35






FOV


than 1000 ft




parallel scan lines




RIEGL RiCOPTER

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



36

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



camera

37

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



38

φi

i

Light

source

Observer

North

φr

r

)(

)()(

ii

rriirrii

E

L

BRDF





F

D A A

B

C E G

O

Honkavaara 2014

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs

wwweurosdrnet



Michael Cramer




wwweurosdrnet








Data Acquisition

RPAS Photogrammetry

=




rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts

41





Distance


Base

xlsquo

xlsquolsquo

Accuracy parameters


ndash Base


bull Measurement

accuracy in image

space




quality


sXY

sZ


Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





Distance Z

Base B

xlsquo

xlsquolsquo

sXY

sZ

43

x X y Y

c Z c Z

x X B y Y

c Z c Z

x

c B c BZ

x x p

y yY Z Z

c c

xX Z

c


Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





Distance Z

Base B

xlsquo

xlsquolsquo



Z b x

Y X b x

Zm

B

m

s s

s s s

sXY

sZ

2

Z Z

x Z b Z

Z B

Zm

c

s s

s s s

Accuracy

44


Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



photogrammetry




xlsquo

xlsquolsquo




sXY

sZ



(analog) airborne






projects

45

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





bull Image scale



XYZ b xq ms s

Z b x

Y X b x

Zm

m

Bs s

s s s


46

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts






11 21 31

13 23 33

12 22 32

13 23 33

r X r Y r Zx z

r X r Y r Z

r X r Y r Zy z

r X r Y r Z

0

0

0

X X X

Y Y Y

Z Z Z

0

0

0

x x x

y y y

z z z c

with 11 12 13

31 32 33

r x r y r zX Z

r x r y r z

21 22 23

31 32 33

r x r y r cY Z

r x r y r c


coordinate frames



coordinates





47

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



0

0

0

X X X

Y Y Y

Z Z Z

0

0

0

x x x

y y y

z z z c


11 21 31

13 23 33

12 22 32

13 23 33

r X r Y r Zx z x

r X r Y r Z

r X r Y r Zy z y

r X r Y r Z









with

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


Camera Calibration





49

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Object coordinate

system

camera

P object point

Plsquo image point


cx

cz

cy

0X

X

)( Rp

p



X

Y

Z

0

l l l Cam

Cam X X R p

50

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




Unit cx

cz

cy

X

Y

Z

bzby

bx


0X

X

)( Rp

p

0

bX

GPS

bX

Cam

bX

e



Object coordinate

system

camera

P object point

Plsquo image point


51

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





Keep in mind





0 l l Cab b b

Ca

m


b b

Cam GPS X X

( )b

Cam R

( ) ( )l n

b b R R

52

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




close-range

53

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Standard-AT

GNSS supported AT

few control points

Calibrated cams +

self-calibration

(math models)

GNSSinertial data



FBMLSM)

RPAS

Few control points

Full in-situ camera

calibration

(physical models

GNSS (code)



(SIFT key points)

camera calibration


up of Image Block


block

Product generation

DTMDSM (Dense

Matching) amp Ortho

Transformation into


Process chain

54

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts










image




55

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




56





x1j

x2j

x3j

Xj

P1

P2

P3

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




copy R Fergus 2014

Incremental SfM

58

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Algorithm






(DLT)



60

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


ca

me

ras

points

61


Algorithm







calibration


new 3D points



triangulation


bundle adjustment

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


ca

me

ras

points

62


Algorithm







calibration


new 3D points



triangulation


bundle adjustment

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Algorithm


rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


Image Matching













64

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts











65






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


EduServ 12 (2014)


66





Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts

wwweurosdrnet



Legal Aspects



Geoinformatik


wwweurosdrnet









69









for subsequent use



rt I-4

ndash L

ega

l Asp

ects




70





rt I-4

ndash L

ega

l Asp

ects





Privacy


apply




72

Pa

rt I-4

ndash L

ega

l Asp

ects







growing


aviation background


before end 2020


73

Pa

rt I-4

ndash L

ega

l Asp

ects



Germany








(Permit required)




74

Pa

rt I-4

ndash L

ega

l Asp

ects


75



77



European Regulation

78





framework






Pa

rt I-4

ndash L

ega

l Asp

ects




79

Pa

rt I-4

ndash L

ega

l Asp

ects



3 Categories

80

Open Category


model planes

and UAS

ndash Geofencing

ndash Subcategories

in relation to

potential harm

ndash Exemption for

toys

ndash Control thru

police

Certified Category


UAS gt 25 kg

bull Certification

similar to

manned aviation

bull Pilot licence

(PPL)


Flight Operation

through Certified

Entities

Specific Category

bull Mostly for

commercial

UAS-users


bull Requirements

depend on use

of operation


Flight Operation)


Entitiesldquo

Pa

rt I-4

ndash L

ega

l Asp

ects



81

Pa

rt I-4

ndash L

ega

l Asp

ects



RPAS segments

82








rt I-4

ndash L

ega

l Asp

ects



RPAS segments









years



83

Pa

rt I-4

ndash L

ega

l Asp

ects


Stabilized mounts

28







Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



29






landing






Quadro copter-Start


rt I-2

ndash S

yste

ms amp

Se

nso

rs



30


their environment



Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



31




navigation



bull Problems


buildings


ndash Expensive

ndash hellip



Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



32









Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



33




ndash Payload 200 g






pilot and Gimbal


Dji Phantom 2

ArduPilot Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



34


RPAS (examples)





Geo referencing




ndash FOV 100deg

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs


RPAS-laser scanning

35






FOV


than 1000 ft




parallel scan lines




RIEGL RiCOPTER

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



36

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



camera

37

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



38

φi

i

Light

source

Observer

North

φr

r

)(

)()(

ii

rriirrii

E

L

BRDF





F

D A A

B

C E G

O

Honkavaara 2014

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs

wwweurosdrnet



Michael Cramer




wwweurosdrnet








Data Acquisition

RPAS Photogrammetry

=




rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts

41





Distance


Base

xlsquo

xlsquolsquo

Accuracy parameters


ndash Base


bull Measurement

accuracy in image

space




quality


sXY

sZ


Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





Distance Z

Base B

xlsquo

xlsquolsquo

sXY

sZ

43

x X y Y

c Z c Z

x X B y Y

c Z c Z

x

c B c BZ

x x p

y yY Z Z

c c

xX Z

c


Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





Distance Z

Base B

xlsquo

xlsquolsquo



Z b x

Y X b x

Zm

B

m

s s

s s s

sXY

sZ

2

Z Z

x Z b Z

Z B

Zm

c

s s

s s s

Accuracy

44


Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



photogrammetry




xlsquo

xlsquolsquo




sXY

sZ



(analog) airborne






projects

45

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





bull Image scale



XYZ b xq ms s

Z b x

Y X b x

Zm

m

Bs s

s s s


46

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts






11 21 31

13 23 33

12 22 32

13 23 33

r X r Y r Zx z

r X r Y r Z

r X r Y r Zy z

r X r Y r Z

0

0

0

X X X

Y Y Y

Z Z Z

0

0

0

x x x

y y y

z z z c

with 11 12 13

31 32 33

r x r y r zX Z

r x r y r z

21 22 23

31 32 33

r x r y r cY Z

r x r y r c


coordinate frames



coordinates





47

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



0

0

0

X X X

Y Y Y

Z Z Z

0

0

0

x x x

y y y

z z z c


11 21 31

13 23 33

12 22 32

13 23 33

r X r Y r Zx z x

r X r Y r Z

r X r Y r Zy z y

r X r Y r Z









with

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


Camera Calibration





49

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Object coordinate

system

camera

P object point

Plsquo image point


cx

cz

cy

0X

X

)( Rp

p



X

Y

Z

0

l l l Cam

Cam X X R p

50

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




Unit cx

cz

cy

X

Y

Z

bzby

bx


0X

X

)( Rp

p

0

bX

GPS

bX

Cam

bX

e



Object coordinate

system

camera

P object point

Plsquo image point


51

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





Keep in mind





0 l l Cab b b

Ca

m


b b

Cam GPS X X

( )b

Cam R

( ) ( )l n

b b R R

52

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




close-range

53

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Standard-AT

GNSS supported AT

few control points

Calibrated cams +

self-calibration

(math models)

GNSSinertial data



FBMLSM)

RPAS

Few control points

Full in-situ camera

calibration

(physical models

GNSS (code)



(SIFT key points)

camera calibration


up of Image Block


block

Product generation

DTMDSM (Dense

Matching) amp Ortho

Transformation into


Process chain

54

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts










image




55

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




56





x1j

x2j

x3j

Xj

P1

P2

P3

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




copy R Fergus 2014

Incremental SfM

58

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Algorithm






(DLT)



60

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


ca

me

ras

points

61


Algorithm







calibration


new 3D points



triangulation


bundle adjustment

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


ca

me

ras

points

62


Algorithm







calibration


new 3D points



triangulation


bundle adjustment

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Algorithm


rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


Image Matching













64

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts











65






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


EduServ 12 (2014)


66





Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts

wwweurosdrnet



Legal Aspects



Geoinformatik


wwweurosdrnet









69









for subsequent use



rt I-4

ndash L

ega

l Asp

ects




70





rt I-4

ndash L

ega

l Asp

ects





Privacy


apply




72

Pa

rt I-4

ndash L

ega

l Asp

ects







growing


aviation background


before end 2020


73

Pa

rt I-4

ndash L

ega

l Asp

ects



Germany








(Permit required)




74

Pa

rt I-4

ndash L

ega

l Asp

ects


75



77



European Regulation

78





framework






Pa

rt I-4

ndash L

ega

l Asp

ects




79

Pa

rt I-4

ndash L

ega

l Asp

ects



3 Categories

80

Open Category


model planes

and UAS

ndash Geofencing

ndash Subcategories

in relation to

potential harm

ndash Exemption for

toys

ndash Control thru

police

Certified Category


UAS gt 25 kg

bull Certification

similar to

manned aviation

bull Pilot licence

(PPL)


Flight Operation

through Certified

Entities

Specific Category

bull Mostly for

commercial

UAS-users


bull Requirements

depend on use

of operation


Flight Operation)


Entitiesldquo

Pa

rt I-4

ndash L

ega

l Asp

ects



81

Pa

rt I-4

ndash L

ega

l Asp

ects



RPAS segments

82








rt I-4

ndash L

ega

l Asp

ects



RPAS segments









years



83

Pa

rt I-4

ndash L

ega

l Asp

ects



29






landing






Quadro copter-Start


rt I-2

ndash S

yste

ms amp

Se

nso

rs



30


their environment



Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



31




navigation



bull Problems


buildings


ndash Expensive

ndash hellip



Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



32









Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



33




ndash Payload 200 g






pilot and Gimbal


Dji Phantom 2

ArduPilot Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



34


RPAS (examples)





Geo referencing




ndash FOV 100deg

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs


RPAS-laser scanning

35






FOV


than 1000 ft




parallel scan lines




RIEGL RiCOPTER

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



36

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



camera

37

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



38

φi

i

Light

source

Observer

North

φr

r

)(

)()(

ii

rriirrii

E

L

BRDF





F

D A A

B

C E G

O

Honkavaara 2014

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs

wwweurosdrnet



Michael Cramer




wwweurosdrnet








Data Acquisition

RPAS Photogrammetry

=




rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts

41





Distance


Base

xlsquo

xlsquolsquo

Accuracy parameters


ndash Base


bull Measurement

accuracy in image

space




quality


sXY

sZ


Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





Distance Z

Base B

xlsquo

xlsquolsquo

sXY

sZ

43

x X y Y

c Z c Z

x X B y Y

c Z c Z

x

c B c BZ

x x p

y yY Z Z

c c

xX Z

c


Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





Distance Z

Base B

xlsquo

xlsquolsquo



Z b x

Y X b x

Zm

B

m

s s

s s s

sXY

sZ

2

Z Z

x Z b Z

Z B

Zm

c

s s

s s s

Accuracy

44


Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



photogrammetry




xlsquo

xlsquolsquo




sXY

sZ



(analog) airborne






projects

45

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





bull Image scale



XYZ b xq ms s

Z b x

Y X b x

Zm

m

Bs s

s s s


46

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts






11 21 31

13 23 33

12 22 32

13 23 33

r X r Y r Zx z

r X r Y r Z

r X r Y r Zy z

r X r Y r Z

0

0

0

X X X

Y Y Y

Z Z Z

0

0

0

x x x

y y y

z z z c

with 11 12 13

31 32 33

r x r y r zX Z

r x r y r z

21 22 23

31 32 33

r x r y r cY Z

r x r y r c


coordinate frames



coordinates





47

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



0

0

0

X X X

Y Y Y

Z Z Z

0

0

0

x x x

y y y

z z z c


11 21 31

13 23 33

12 22 32

13 23 33

r X r Y r Zx z x

r X r Y r Z

r X r Y r Zy z y

r X r Y r Z









with

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


Camera Calibration





49

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Object coordinate

system

camera

P object point

Plsquo image point


cx

cz

cy

0X

X

)( Rp

p



X

Y

Z

0

l l l Cam

Cam X X R p

50

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




Unit cx

cz

cy

X

Y

Z

bzby

bx


0X

X

)( Rp

p

0

bX

GPS

bX

Cam

bX

e



Object coordinate

system

camera

P object point

Plsquo image point


51

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





Keep in mind





0 l l Cab b b

Ca

m


b b

Cam GPS X X

( )b

Cam R

( ) ( )l n

b b R R

52

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




close-range

53

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Standard-AT

GNSS supported AT

few control points

Calibrated cams +

self-calibration

(math models)

GNSSinertial data



FBMLSM)

RPAS

Few control points

Full in-situ camera

calibration

(physical models

GNSS (code)



(SIFT key points)

camera calibration


up of Image Block


block

Product generation

DTMDSM (Dense

Matching) amp Ortho

Transformation into


Process chain

54

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts










image




55

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




56





x1j

x2j

x3j

Xj

P1

P2

P3

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




copy R Fergus 2014

Incremental SfM

58

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Algorithm






(DLT)



60

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


ca

me

ras

points

61


Algorithm







calibration


new 3D points



triangulation


bundle adjustment

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


ca

me

ras

points

62


Algorithm







calibration


new 3D points



triangulation


bundle adjustment

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Algorithm


rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


Image Matching













64

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts











65






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


EduServ 12 (2014)


66





Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts

wwweurosdrnet



Legal Aspects



Geoinformatik


wwweurosdrnet









69









for subsequent use



rt I-4

ndash L

ega

l Asp

ects




70





rt I-4

ndash L

ega

l Asp

ects





Privacy


apply




72

Pa

rt I-4

ndash L

ega

l Asp

ects







growing


aviation background


before end 2020


73

Pa

rt I-4

ndash L

ega

l Asp

ects



Germany








(Permit required)




74

Pa

rt I-4

ndash L

ega

l Asp

ects


75



77



European Regulation

78





framework






Pa

rt I-4

ndash L

ega

l Asp

ects




79

Pa

rt I-4

ndash L

ega

l Asp

ects



3 Categories

80

Open Category


model planes

and UAS

ndash Geofencing

ndash Subcategories

in relation to

potential harm

ndash Exemption for

toys

ndash Control thru

police

Certified Category


UAS gt 25 kg

bull Certification

similar to

manned aviation

bull Pilot licence

(PPL)


Flight Operation

through Certified

Entities

Specific Category

bull Mostly for

commercial

UAS-users


bull Requirements

depend on use

of operation


Flight Operation)


Entitiesldquo

Pa

rt I-4

ndash L

ega

l Asp

ects



81

Pa

rt I-4

ndash L

ega

l Asp

ects



RPAS segments

82








rt I-4

ndash L

ega

l Asp

ects



RPAS segments









years



83

Pa

rt I-4

ndash L

ega

l Asp

ects



30


their environment



Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



31




navigation



bull Problems


buildings


ndash Expensive

ndash hellip



Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



32









Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



33




ndash Payload 200 g






pilot and Gimbal


Dji Phantom 2

ArduPilot Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



34


RPAS (examples)





Geo referencing




ndash FOV 100deg

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs


RPAS-laser scanning

35






FOV


than 1000 ft




parallel scan lines




RIEGL RiCOPTER

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



36

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



camera

37

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



38

φi

i

Light

source

Observer

North

φr

r

)(

)()(

ii

rriirrii

E

L

BRDF





F

D A A

B

C E G

O

Honkavaara 2014

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs

wwweurosdrnet



Michael Cramer




wwweurosdrnet








Data Acquisition

RPAS Photogrammetry

=




rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts

41





Distance


Base

xlsquo

xlsquolsquo

Accuracy parameters


ndash Base


bull Measurement

accuracy in image

space




quality


sXY

sZ


Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





Distance Z

Base B

xlsquo

xlsquolsquo

sXY

sZ

43

x X y Y

c Z c Z

x X B y Y

c Z c Z

x

c B c BZ

x x p

y yY Z Z

c c

xX Z

c


Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





Distance Z

Base B

xlsquo

xlsquolsquo



Z b x

Y X b x

Zm

B

m

s s

s s s

sXY

sZ

2

Z Z

x Z b Z

Z B

Zm

c

s s

s s s

Accuracy

44


Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



photogrammetry




xlsquo

xlsquolsquo




sXY

sZ



(analog) airborne






projects

45

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





bull Image scale



XYZ b xq ms s

Z b x

Y X b x

Zm

m

Bs s

s s s


46

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts






11 21 31

13 23 33

12 22 32

13 23 33

r X r Y r Zx z

r X r Y r Z

r X r Y r Zy z

r X r Y r Z

0

0

0

X X X

Y Y Y

Z Z Z

0

0

0

x x x

y y y

z z z c

with 11 12 13

31 32 33

r x r y r zX Z

r x r y r z

21 22 23

31 32 33

r x r y r cY Z

r x r y r c


coordinate frames



coordinates





47

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



0

0

0

X X X

Y Y Y

Z Z Z

0

0

0

x x x

y y y

z z z c


11 21 31

13 23 33

12 22 32

13 23 33

r X r Y r Zx z x

r X r Y r Z

r X r Y r Zy z y

r X r Y r Z









with

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


Camera Calibration





49

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Object coordinate

system

camera

P object point

Plsquo image point


cx

cz

cy

0X

X

)( Rp

p



X

Y

Z

0

l l l Cam

Cam X X R p

50

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




Unit cx

cz

cy

X

Y

Z

bzby

bx


0X

X

)( Rp

p

0

bX

GPS

bX

Cam

bX

e



Object coordinate

system

camera

P object point

Plsquo image point


51

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





Keep in mind





0 l l Cab b b

Ca

m


b b

Cam GPS X X

( )b

Cam R

( ) ( )l n

b b R R

52

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




close-range

53

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Standard-AT

GNSS supported AT

few control points

Calibrated cams +

self-calibration

(math models)

GNSSinertial data



FBMLSM)

RPAS

Few control points

Full in-situ camera

calibration

(physical models

GNSS (code)



(SIFT key points)

camera calibration


up of Image Block


block

Product generation

DTMDSM (Dense

Matching) amp Ortho

Transformation into


Process chain

54

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts










image




55

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




56





x1j

x2j

x3j

Xj

P1

P2

P3

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




copy R Fergus 2014

Incremental SfM

58

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Algorithm






(DLT)



60

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


ca

me

ras

points

61


Algorithm







calibration


new 3D points



triangulation


bundle adjustment

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


ca

me

ras

points

62


Algorithm







calibration


new 3D points



triangulation


bundle adjustment

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Algorithm


rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


Image Matching













64

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts











65






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


EduServ 12 (2014)


66





Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts

wwweurosdrnet



Legal Aspects



Geoinformatik


wwweurosdrnet









69









for subsequent use



rt I-4

ndash L

ega

l Asp

ects




70





rt I-4

ndash L

ega

l Asp

ects





Privacy


apply




72

Pa

rt I-4

ndash L

ega

l Asp

ects







growing


aviation background


before end 2020


73

Pa

rt I-4

ndash L

ega

l Asp

ects



Germany








(Permit required)




74

Pa

rt I-4

ndash L

ega

l Asp

ects


75



77



European Regulation

78





framework






Pa

rt I-4

ndash L

ega

l Asp

ects




79

Pa

rt I-4

ndash L

ega

l Asp

ects



3 Categories

80

Open Category


model planes

and UAS

ndash Geofencing

ndash Subcategories

in relation to

potential harm

ndash Exemption for

toys

ndash Control thru

police

Certified Category


UAS gt 25 kg

bull Certification

similar to

manned aviation

bull Pilot licence

(PPL)


Flight Operation

through Certified

Entities

Specific Category

bull Mostly for

commercial

UAS-users


bull Requirements

depend on use

of operation


Flight Operation)


Entitiesldquo

Pa

rt I-4

ndash L

ega

l Asp

ects



81

Pa

rt I-4

ndash L

ega

l Asp

ects



RPAS segments

82








rt I-4

ndash L

ega

l Asp

ects



RPAS segments









years



83

Pa

rt I-4

ndash L

ega

l Asp

ects



31




navigation



bull Problems


buildings


ndash Expensive

ndash hellip



Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



32









Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



33




ndash Payload 200 g






pilot and Gimbal


Dji Phantom 2

ArduPilot Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



34


RPAS (examples)





Geo referencing




ndash FOV 100deg

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs


RPAS-laser scanning

35






FOV


than 1000 ft




parallel scan lines




RIEGL RiCOPTER

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



36

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



camera

37

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



38

φi

i

Light

source

Observer

North

φr

r

)(

)()(

ii

rriirrii

E

L

BRDF





F

D A A

B

C E G

O

Honkavaara 2014

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs

wwweurosdrnet



Michael Cramer




wwweurosdrnet








Data Acquisition

RPAS Photogrammetry

=




rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts

41





Distance


Base

xlsquo

xlsquolsquo

Accuracy parameters


ndash Base


bull Measurement

accuracy in image

space




quality


sXY

sZ


Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





Distance Z

Base B

xlsquo

xlsquolsquo

sXY

sZ

43

x X y Y

c Z c Z

x X B y Y

c Z c Z

x

c B c BZ

x x p

y yY Z Z

c c

xX Z

c


Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





Distance Z

Base B

xlsquo

xlsquolsquo



Z b x

Y X b x

Zm

B

m

s s

s s s

sXY

sZ

2

Z Z

x Z b Z

Z B

Zm

c

s s

s s s

Accuracy

44


Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



photogrammetry




xlsquo

xlsquolsquo




sXY

sZ



(analog) airborne






projects

45

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





bull Image scale



XYZ b xq ms s

Z b x

Y X b x

Zm

m

Bs s

s s s


46

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts






11 21 31

13 23 33

12 22 32

13 23 33

r X r Y r Zx z

r X r Y r Z

r X r Y r Zy z

r X r Y r Z

0

0

0

X X X

Y Y Y

Z Z Z

0

0

0

x x x

y y y

z z z c

with 11 12 13

31 32 33

r x r y r zX Z

r x r y r z

21 22 23

31 32 33

r x r y r cY Z

r x r y r c


coordinate frames



coordinates





47

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



0

0

0

X X X

Y Y Y

Z Z Z

0

0

0

x x x

y y y

z z z c


11 21 31

13 23 33

12 22 32

13 23 33

r X r Y r Zx z x

r X r Y r Z

r X r Y r Zy z y

r X r Y r Z









with

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


Camera Calibration





49

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Object coordinate

system

camera

P object point

Plsquo image point


cx

cz

cy

0X

X

)( Rp

p



X

Y

Z

0

l l l Cam

Cam X X R p

50

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




Unit cx

cz

cy

X

Y

Z

bzby

bx


0X

X

)( Rp

p

0

bX

GPS

bX

Cam

bX

e



Object coordinate

system

camera

P object point

Plsquo image point


51

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





Keep in mind





0 l l Cab b b

Ca

m


b b

Cam GPS X X

( )b

Cam R

( ) ( )l n

b b R R

52

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




close-range

53

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Standard-AT

GNSS supported AT

few control points

Calibrated cams +

self-calibration

(math models)

GNSSinertial data



FBMLSM)

RPAS

Few control points

Full in-situ camera

calibration

(physical models

GNSS (code)



(SIFT key points)

camera calibration


up of Image Block


block

Product generation

DTMDSM (Dense

Matching) amp Ortho

Transformation into


Process chain

54

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts










image




55

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




56





x1j

x2j

x3j

Xj

P1

P2

P3

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




copy R Fergus 2014

Incremental SfM

58

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Algorithm






(DLT)



60

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


ca

me

ras

points

61


Algorithm







calibration


new 3D points



triangulation


bundle adjustment

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


ca

me

ras

points

62


Algorithm







calibration


new 3D points



triangulation


bundle adjustment

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Algorithm


rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


Image Matching













64

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts











65






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


EduServ 12 (2014)


66





Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts

wwweurosdrnet



Legal Aspects



Geoinformatik


wwweurosdrnet









69









for subsequent use



rt I-4

ndash L

ega

l Asp

ects




70





rt I-4

ndash L

ega

l Asp

ects





Privacy


apply




72

Pa

rt I-4

ndash L

ega

l Asp

ects







growing


aviation background


before end 2020


73

Pa

rt I-4

ndash L

ega

l Asp

ects



Germany








(Permit required)




74

Pa

rt I-4

ndash L

ega

l Asp

ects


75



77



European Regulation

78





framework






Pa

rt I-4

ndash L

ega

l Asp

ects




79

Pa

rt I-4

ndash L

ega

l Asp

ects



3 Categories

80

Open Category


model planes

and UAS

ndash Geofencing

ndash Subcategories

in relation to

potential harm

ndash Exemption for

toys

ndash Control thru

police

Certified Category


UAS gt 25 kg

bull Certification

similar to

manned aviation

bull Pilot licence

(PPL)


Flight Operation

through Certified

Entities

Specific Category

bull Mostly for

commercial

UAS-users


bull Requirements

depend on use

of operation


Flight Operation)


Entitiesldquo

Pa

rt I-4

ndash L

ega

l Asp

ects



81

Pa

rt I-4

ndash L

ega

l Asp

ects



RPAS segments

82








rt I-4

ndash L

ega

l Asp

ects



RPAS segments









years



83

Pa

rt I-4

ndash L

ega

l Asp

ects



32









Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



33




ndash Payload 200 g






pilot and Gimbal


Dji Phantom 2

ArduPilot Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



34


RPAS (examples)





Geo referencing




ndash FOV 100deg

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs


RPAS-laser scanning

35






FOV


than 1000 ft




parallel scan lines




RIEGL RiCOPTER

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



36

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



camera

37

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



38

φi

i

Light

source

Observer

North

φr

r

)(

)()(

ii

rriirrii

E

L

BRDF





F

D A A

B

C E G

O

Honkavaara 2014

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs

wwweurosdrnet



Michael Cramer




wwweurosdrnet








Data Acquisition

RPAS Photogrammetry

=




rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts

41





Distance


Base

xlsquo

xlsquolsquo

Accuracy parameters


ndash Base


bull Measurement

accuracy in image

space




quality


sXY

sZ


Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





Distance Z

Base B

xlsquo

xlsquolsquo

sXY

sZ

43

x X y Y

c Z c Z

x X B y Y

c Z c Z

x

c B c BZ

x x p

y yY Z Z

c c

xX Z

c


Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





Distance Z

Base B

xlsquo

xlsquolsquo



Z b x

Y X b x

Zm

B

m

s s

s s s

sXY

sZ

2

Z Z

x Z b Z

Z B

Zm

c

s s

s s s

Accuracy

44


Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



photogrammetry




xlsquo

xlsquolsquo




sXY

sZ



(analog) airborne






projects

45

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





bull Image scale



XYZ b xq ms s

Z b x

Y X b x

Zm

m

Bs s

s s s


46

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts






11 21 31

13 23 33

12 22 32

13 23 33

r X r Y r Zx z

r X r Y r Z

r X r Y r Zy z

r X r Y r Z

0

0

0

X X X

Y Y Y

Z Z Z

0

0

0

x x x

y y y

z z z c

with 11 12 13

31 32 33

r x r y r zX Z

r x r y r z

21 22 23

31 32 33

r x r y r cY Z

r x r y r c


coordinate frames



coordinates





47

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



0

0

0

X X X

Y Y Y

Z Z Z

0

0

0

x x x

y y y

z z z c


11 21 31

13 23 33

12 22 32

13 23 33

r X r Y r Zx z x

r X r Y r Z

r X r Y r Zy z y

r X r Y r Z









with

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


Camera Calibration





49

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Object coordinate

system

camera

P object point

Plsquo image point


cx

cz

cy

0X

X

)( Rp

p



X

Y

Z

0

l l l Cam

Cam X X R p

50

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




Unit cx

cz

cy

X

Y

Z

bzby

bx


0X

X

)( Rp

p

0

bX

GPS

bX

Cam

bX

e



Object coordinate

system

camera

P object point

Plsquo image point


51

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





Keep in mind





0 l l Cab b b

Ca

m


b b

Cam GPS X X

( )b

Cam R

( ) ( )l n

b b R R

52

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




close-range

53

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Standard-AT

GNSS supported AT

few control points

Calibrated cams +

self-calibration

(math models)

GNSSinertial data



FBMLSM)

RPAS

Few control points

Full in-situ camera

calibration

(physical models

GNSS (code)



(SIFT key points)

camera calibration


up of Image Block


block

Product generation

DTMDSM (Dense

Matching) amp Ortho

Transformation into


Process chain

54

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts










image




55

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




56





x1j

x2j

x3j

Xj

P1

P2

P3

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




copy R Fergus 2014

Incremental SfM

58

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Algorithm






(DLT)



60

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


ca

me

ras

points

61


Algorithm







calibration


new 3D points



triangulation


bundle adjustment

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


ca

me

ras

points

62


Algorithm







calibration


new 3D points



triangulation


bundle adjustment

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Algorithm


rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


Image Matching













64

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts











65






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


EduServ 12 (2014)


66





Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts

wwweurosdrnet



Legal Aspects



Geoinformatik


wwweurosdrnet









69









for subsequent use



rt I-4

ndash L

ega

l Asp

ects




70





rt I-4

ndash L

ega

l Asp

ects





Privacy


apply




72

Pa

rt I-4

ndash L

ega

l Asp

ects







growing


aviation background


before end 2020


73

Pa

rt I-4

ndash L

ega

l Asp

ects



Germany








(Permit required)




74

Pa

rt I-4

ndash L

ega

l Asp

ects


75



77



European Regulation

78





framework






Pa

rt I-4

ndash L

ega

l Asp

ects




79

Pa

rt I-4

ndash L

ega

l Asp

ects



3 Categories

80

Open Category


model planes

and UAS

ndash Geofencing

ndash Subcategories

in relation to

potential harm

ndash Exemption for

toys

ndash Control thru

police

Certified Category


UAS gt 25 kg

bull Certification

similar to

manned aviation

bull Pilot licence

(PPL)


Flight Operation

through Certified

Entities

Specific Category

bull Mostly for

commercial

UAS-users


bull Requirements

depend on use

of operation


Flight Operation)


Entitiesldquo

Pa

rt I-4

ndash L

ega

l Asp

ects



81

Pa

rt I-4

ndash L

ega

l Asp

ects



RPAS segments

82








rt I-4

ndash L

ega

l Asp

ects



RPAS segments









years



83

Pa

rt I-4

ndash L

ega

l Asp

ects



33




ndash Payload 200 g






pilot and Gimbal


Dji Phantom 2

ArduPilot Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



34


RPAS (examples)





Geo referencing




ndash FOV 100deg

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs


RPAS-laser scanning

35






FOV


than 1000 ft




parallel scan lines




RIEGL RiCOPTER

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



36

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



camera

37

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



38

φi

i

Light

source

Observer

North

φr

r

)(

)()(

ii

rriirrii

E

L

BRDF





F

D A A

B

C E G

O

Honkavaara 2014

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs

wwweurosdrnet



Michael Cramer




wwweurosdrnet








Data Acquisition

RPAS Photogrammetry

=




rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts

41





Distance


Base

xlsquo

xlsquolsquo

Accuracy parameters


ndash Base


bull Measurement

accuracy in image

space




quality


sXY

sZ


Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





Distance Z

Base B

xlsquo

xlsquolsquo

sXY

sZ

43

x X y Y

c Z c Z

x X B y Y

c Z c Z

x

c B c BZ

x x p

y yY Z Z

c c

xX Z

c


Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





Distance Z

Base B

xlsquo

xlsquolsquo



Z b x

Y X b x

Zm

B

m

s s

s s s

sXY

sZ

2

Z Z

x Z b Z

Z B

Zm

c

s s

s s s

Accuracy

44


Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



photogrammetry




xlsquo

xlsquolsquo




sXY

sZ



(analog) airborne






projects

45

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





bull Image scale



XYZ b xq ms s

Z b x

Y X b x

Zm

m

Bs s

s s s


46

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts






11 21 31

13 23 33

12 22 32

13 23 33

r X r Y r Zx z

r X r Y r Z

r X r Y r Zy z

r X r Y r Z

0

0

0

X X X

Y Y Y

Z Z Z

0

0

0

x x x

y y y

z z z c

with 11 12 13

31 32 33

r x r y r zX Z

r x r y r z

21 22 23

31 32 33

r x r y r cY Z

r x r y r c


coordinate frames



coordinates





47

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



0

0

0

X X X

Y Y Y

Z Z Z

0

0

0

x x x

y y y

z z z c


11 21 31

13 23 33

12 22 32

13 23 33

r X r Y r Zx z x

r X r Y r Z

r X r Y r Zy z y

r X r Y r Z









with

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


Camera Calibration





49

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Object coordinate

system

camera

P object point

Plsquo image point


cx

cz

cy

0X

X

)( Rp

p



X

Y

Z

0

l l l Cam

Cam X X R p

50

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




Unit cx

cz

cy

X

Y

Z

bzby

bx


0X

X

)( Rp

p

0

bX

GPS

bX

Cam

bX

e



Object coordinate

system

camera

P object point

Plsquo image point


51

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





Keep in mind





0 l l Cab b b

Ca

m


b b

Cam GPS X X

( )b

Cam R

( ) ( )l n

b b R R

52

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




close-range

53

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Standard-AT

GNSS supported AT

few control points

Calibrated cams +

self-calibration

(math models)

GNSSinertial data



FBMLSM)

RPAS

Few control points

Full in-situ camera

calibration

(physical models

GNSS (code)



(SIFT key points)

camera calibration


up of Image Block


block

Product generation

DTMDSM (Dense

Matching) amp Ortho

Transformation into


Process chain

54

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts










image




55

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




56





x1j

x2j

x3j

Xj

P1

P2

P3

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




copy R Fergus 2014

Incremental SfM

58

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Algorithm






(DLT)



60

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


ca

me

ras

points

61


Algorithm







calibration


new 3D points



triangulation


bundle adjustment

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


ca

me

ras

points

62


Algorithm







calibration


new 3D points



triangulation


bundle adjustment

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Algorithm


rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


Image Matching













64

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts











65






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


EduServ 12 (2014)


66





Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts

wwweurosdrnet



Legal Aspects



Geoinformatik


wwweurosdrnet









69









for subsequent use



rt I-4

ndash L

ega

l Asp

ects




70





rt I-4

ndash L

ega

l Asp

ects





Privacy


apply




72

Pa

rt I-4

ndash L

ega

l Asp

ects







growing


aviation background


before end 2020


73

Pa

rt I-4

ndash L

ega

l Asp

ects



Germany








(Permit required)




74

Pa

rt I-4

ndash L

ega

l Asp

ects


75



77



European Regulation

78





framework






Pa

rt I-4

ndash L

ega

l Asp

ects




79

Pa

rt I-4

ndash L

ega

l Asp

ects



3 Categories

80

Open Category


model planes

and UAS

ndash Geofencing

ndash Subcategories

in relation to

potential harm

ndash Exemption for

toys

ndash Control thru

police

Certified Category


UAS gt 25 kg

bull Certification

similar to

manned aviation

bull Pilot licence

(PPL)


Flight Operation

through Certified

Entities

Specific Category

bull Mostly for

commercial

UAS-users


bull Requirements

depend on use

of operation


Flight Operation)


Entitiesldquo

Pa

rt I-4

ndash L

ega

l Asp

ects



81

Pa

rt I-4

ndash L

ega

l Asp

ects



RPAS segments

82








rt I-4

ndash L

ega

l Asp

ects



RPAS segments









years



83

Pa

rt I-4

ndash L

ega

l Asp

ects



34


RPAS (examples)





Geo referencing




ndash FOV 100deg

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs


RPAS-laser scanning

35






FOV


than 1000 ft




parallel scan lines




RIEGL RiCOPTER

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



36

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



camera

37

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



38

φi

i

Light

source

Observer

North

φr

r

)(

)()(

ii

rriirrii

E

L

BRDF





F

D A A

B

C E G

O

Honkavaara 2014

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs

wwweurosdrnet



Michael Cramer




wwweurosdrnet








Data Acquisition

RPAS Photogrammetry

=




rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts

41





Distance


Base

xlsquo

xlsquolsquo

Accuracy parameters


ndash Base


bull Measurement

accuracy in image

space




quality


sXY

sZ


Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





Distance Z

Base B

xlsquo

xlsquolsquo

sXY

sZ

43

x X y Y

c Z c Z

x X B y Y

c Z c Z

x

c B c BZ

x x p

y yY Z Z

c c

xX Z

c


Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





Distance Z

Base B

xlsquo

xlsquolsquo



Z b x

Y X b x

Zm

B

m

s s

s s s

sXY

sZ

2

Z Z

x Z b Z

Z B

Zm

c

s s

s s s

Accuracy

44


Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



photogrammetry




xlsquo

xlsquolsquo




sXY

sZ



(analog) airborne






projects

45

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





bull Image scale



XYZ b xq ms s

Z b x

Y X b x

Zm

m

Bs s

s s s


46

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts






11 21 31

13 23 33

12 22 32

13 23 33

r X r Y r Zx z

r X r Y r Z

r X r Y r Zy z

r X r Y r Z

0

0

0

X X X

Y Y Y

Z Z Z

0

0

0

x x x

y y y

z z z c

with 11 12 13

31 32 33

r x r y r zX Z

r x r y r z

21 22 23

31 32 33

r x r y r cY Z

r x r y r c


coordinate frames



coordinates





47

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



0

0

0

X X X

Y Y Y

Z Z Z

0

0

0

x x x

y y y

z z z c


11 21 31

13 23 33

12 22 32

13 23 33

r X r Y r Zx z x

r X r Y r Z

r X r Y r Zy z y

r X r Y r Z









with

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


Camera Calibration





49

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Object coordinate

system

camera

P object point

Plsquo image point


cx

cz

cy

0X

X

)( Rp

p



X

Y

Z

0

l l l Cam

Cam X X R p

50

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




Unit cx

cz

cy

X

Y

Z

bzby

bx


0X

X

)( Rp

p

0

bX

GPS

bX

Cam

bX

e



Object coordinate

system

camera

P object point

Plsquo image point


51

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





Keep in mind





0 l l Cab b b

Ca

m


b b

Cam GPS X X

( )b

Cam R

( ) ( )l n

b b R R

52

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




close-range

53

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Standard-AT

GNSS supported AT

few control points

Calibrated cams +

self-calibration

(math models)

GNSSinertial data



FBMLSM)

RPAS

Few control points

Full in-situ camera

calibration

(physical models

GNSS (code)



(SIFT key points)

camera calibration


up of Image Block


block

Product generation

DTMDSM (Dense

Matching) amp Ortho

Transformation into


Process chain

54

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts










image




55

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




56





x1j

x2j

x3j

Xj

P1

P2

P3

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




copy R Fergus 2014

Incremental SfM

58

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Algorithm






(DLT)



60

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


ca

me

ras

points

61


Algorithm







calibration


new 3D points



triangulation


bundle adjustment

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


ca

me

ras

points

62


Algorithm







calibration


new 3D points



triangulation


bundle adjustment

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Algorithm


rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


Image Matching













64

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts











65






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


EduServ 12 (2014)


66





Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts

wwweurosdrnet



Legal Aspects



Geoinformatik


wwweurosdrnet









69









for subsequent use



rt I-4

ndash L

ega

l Asp

ects




70





rt I-4

ndash L

ega

l Asp

ects





Privacy


apply




72

Pa

rt I-4

ndash L

ega

l Asp

ects







growing


aviation background


before end 2020


73

Pa

rt I-4

ndash L

ega

l Asp

ects



Germany








(Permit required)




74

Pa

rt I-4

ndash L

ega

l Asp

ects


75



77



European Regulation

78





framework






Pa

rt I-4

ndash L

ega

l Asp

ects




79

Pa

rt I-4

ndash L

ega

l Asp

ects



3 Categories

80

Open Category


model planes

and UAS

ndash Geofencing

ndash Subcategories

in relation to

potential harm

ndash Exemption for

toys

ndash Control thru

police

Certified Category


UAS gt 25 kg

bull Certification

similar to

manned aviation

bull Pilot licence

(PPL)


Flight Operation

through Certified

Entities

Specific Category

bull Mostly for

commercial

UAS-users


bull Requirements

depend on use

of operation


Flight Operation)


Entitiesldquo

Pa

rt I-4

ndash L

ega

l Asp

ects



81

Pa

rt I-4

ndash L

ega

l Asp

ects



RPAS segments

82








rt I-4

ndash L

ega

l Asp

ects



RPAS segments









years



83

Pa

rt I-4

ndash L

ega

l Asp

ects


RPAS-laser scanning

35






FOV


than 1000 ft




parallel scan lines




RIEGL RiCOPTER

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



36

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



camera

37

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



38

φi

i

Light

source

Observer

North

φr

r

)(

)()(

ii

rriirrii

E

L

BRDF





F

D A A

B

C E G

O

Honkavaara 2014

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs

wwweurosdrnet



Michael Cramer




wwweurosdrnet








Data Acquisition

RPAS Photogrammetry

=




rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts

41





Distance


Base

xlsquo

xlsquolsquo

Accuracy parameters


ndash Base


bull Measurement

accuracy in image

space




quality


sXY

sZ


Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





Distance Z

Base B

xlsquo

xlsquolsquo

sXY

sZ

43

x X y Y

c Z c Z

x X B y Y

c Z c Z

x

c B c BZ

x x p

y yY Z Z

c c

xX Z

c


Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





Distance Z

Base B

xlsquo

xlsquolsquo



Z b x

Y X b x

Zm

B

m

s s

s s s

sXY

sZ

2

Z Z

x Z b Z

Z B

Zm

c

s s

s s s

Accuracy

44


Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



photogrammetry




xlsquo

xlsquolsquo




sXY

sZ



(analog) airborne






projects

45

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





bull Image scale



XYZ b xq ms s

Z b x

Y X b x

Zm

m

Bs s

s s s


46

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts






11 21 31

13 23 33

12 22 32

13 23 33

r X r Y r Zx z

r X r Y r Z

r X r Y r Zy z

r X r Y r Z

0

0

0

X X X

Y Y Y

Z Z Z

0

0

0

x x x

y y y

z z z c

with 11 12 13

31 32 33

r x r y r zX Z

r x r y r z

21 22 23

31 32 33

r x r y r cY Z

r x r y r c


coordinate frames



coordinates





47

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



0

0

0

X X X

Y Y Y

Z Z Z

0

0

0

x x x

y y y

z z z c


11 21 31

13 23 33

12 22 32

13 23 33

r X r Y r Zx z x

r X r Y r Z

r X r Y r Zy z y

r X r Y r Z









with

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


Camera Calibration





49

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Object coordinate

system

camera

P object point

Plsquo image point


cx

cz

cy

0X

X

)( Rp

p



X

Y

Z

0

l l l Cam

Cam X X R p

50

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




Unit cx

cz

cy

X

Y

Z

bzby

bx


0X

X

)( Rp

p

0

bX

GPS

bX

Cam

bX

e



Object coordinate

system

camera

P object point

Plsquo image point


51

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





Keep in mind





0 l l Cab b b

Ca

m


b b

Cam GPS X X

( )b

Cam R

( ) ( )l n

b b R R

52

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




close-range

53

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Standard-AT

GNSS supported AT

few control points

Calibrated cams +

self-calibration

(math models)

GNSSinertial data



FBMLSM)

RPAS

Few control points

Full in-situ camera

calibration

(physical models

GNSS (code)



(SIFT key points)

camera calibration


up of Image Block


block

Product generation

DTMDSM (Dense

Matching) amp Ortho

Transformation into


Process chain

54

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts










image




55

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




56





x1j

x2j

x3j

Xj

P1

P2

P3

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




copy R Fergus 2014

Incremental SfM

58

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Algorithm






(DLT)



60

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


ca

me

ras

points

61


Algorithm







calibration


new 3D points



triangulation


bundle adjustment

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


ca

me

ras

points

62


Algorithm







calibration


new 3D points



triangulation


bundle adjustment

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Algorithm


rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


Image Matching













64

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts











65






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


EduServ 12 (2014)


66





Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts

wwweurosdrnet



Legal Aspects



Geoinformatik


wwweurosdrnet









69









for subsequent use



rt I-4

ndash L

ega

l Asp

ects




70





rt I-4

ndash L

ega

l Asp

ects





Privacy


apply




72

Pa

rt I-4

ndash L

ega

l Asp

ects







growing


aviation background


before end 2020


73

Pa

rt I-4

ndash L

ega

l Asp

ects



Germany








(Permit required)




74

Pa

rt I-4

ndash L

ega

l Asp

ects


75



77



European Regulation

78





framework






Pa

rt I-4

ndash L

ega

l Asp

ects




79

Pa

rt I-4

ndash L

ega

l Asp

ects



3 Categories

80

Open Category


model planes

and UAS

ndash Geofencing

ndash Subcategories

in relation to

potential harm

ndash Exemption for

toys

ndash Control thru

police

Certified Category


UAS gt 25 kg

bull Certification

similar to

manned aviation

bull Pilot licence

(PPL)


Flight Operation

through Certified

Entities

Specific Category

bull Mostly for

commercial

UAS-users


bull Requirements

depend on use

of operation


Flight Operation)


Entitiesldquo

Pa

rt I-4

ndash L

ega

l Asp

ects



81

Pa

rt I-4

ndash L

ega

l Asp

ects



RPAS segments

82








rt I-4

ndash L

ega

l Asp

ects



RPAS segments









years



83

Pa

rt I-4

ndash L

ega

l Asp

ects



36

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



camera

37

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



38

φi

i

Light

source

Observer

North

φr

r

)(

)()(

ii

rriirrii

E

L

BRDF





F

D A A

B

C E G

O

Honkavaara 2014

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs

wwweurosdrnet



Michael Cramer




wwweurosdrnet








Data Acquisition

RPAS Photogrammetry

=




rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts

41





Distance


Base

xlsquo

xlsquolsquo

Accuracy parameters


ndash Base


bull Measurement

accuracy in image

space




quality


sXY

sZ


Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





Distance Z

Base B

xlsquo

xlsquolsquo

sXY

sZ

43

x X y Y

c Z c Z

x X B y Y

c Z c Z

x

c B c BZ

x x p

y yY Z Z

c c

xX Z

c


Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





Distance Z

Base B

xlsquo

xlsquolsquo



Z b x

Y X b x

Zm

B

m

s s

s s s

sXY

sZ

2

Z Z

x Z b Z

Z B

Zm

c

s s

s s s

Accuracy

44


Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



photogrammetry




xlsquo

xlsquolsquo




sXY

sZ



(analog) airborne






projects

45

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





bull Image scale



XYZ b xq ms s

Z b x

Y X b x

Zm

m

Bs s

s s s


46

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts






11 21 31

13 23 33

12 22 32

13 23 33

r X r Y r Zx z

r X r Y r Z

r X r Y r Zy z

r X r Y r Z

0

0

0

X X X

Y Y Y

Z Z Z

0

0

0

x x x

y y y

z z z c

with 11 12 13

31 32 33

r x r y r zX Z

r x r y r z

21 22 23

31 32 33

r x r y r cY Z

r x r y r c


coordinate frames



coordinates





47

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



0

0

0

X X X

Y Y Y

Z Z Z

0

0

0

x x x

y y y

z z z c


11 21 31

13 23 33

12 22 32

13 23 33

r X r Y r Zx z x

r X r Y r Z

r X r Y r Zy z y

r X r Y r Z









with

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


Camera Calibration





49

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Object coordinate

system

camera

P object point

Plsquo image point


cx

cz

cy

0X

X

)( Rp

p



X

Y

Z

0

l l l Cam

Cam X X R p

50

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




Unit cx

cz

cy

X

Y

Z

bzby

bx


0X

X

)( Rp

p

0

bX

GPS

bX

Cam

bX

e



Object coordinate

system

camera

P object point

Plsquo image point


51

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





Keep in mind





0 l l Cab b b

Ca

m


b b

Cam GPS X X

( )b

Cam R

( ) ( )l n

b b R R

52

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




close-range

53

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Standard-AT

GNSS supported AT

few control points

Calibrated cams +

self-calibration

(math models)

GNSSinertial data



FBMLSM)

RPAS

Few control points

Full in-situ camera

calibration

(physical models

GNSS (code)



(SIFT key points)

camera calibration


up of Image Block


block

Product generation

DTMDSM (Dense

Matching) amp Ortho

Transformation into


Process chain

54

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts










image




55

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




56





x1j

x2j

x3j

Xj

P1

P2

P3

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




copy R Fergus 2014

Incremental SfM

58

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Algorithm






(DLT)



60

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


ca

me

ras

points

61


Algorithm







calibration


new 3D points



triangulation


bundle adjustment

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


ca

me

ras

points

62


Algorithm







calibration


new 3D points



triangulation


bundle adjustment

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Algorithm


rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


Image Matching













64

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts











65






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


EduServ 12 (2014)


66





Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts

wwweurosdrnet



Legal Aspects



Geoinformatik


wwweurosdrnet









69









for subsequent use



rt I-4

ndash L

ega

l Asp

ects




70





rt I-4

ndash L

ega

l Asp

ects





Privacy


apply




72

Pa

rt I-4

ndash L

ega

l Asp

ects







growing


aviation background


before end 2020


73

Pa

rt I-4

ndash L

ega

l Asp

ects



Germany








(Permit required)




74

Pa

rt I-4

ndash L

ega

l Asp

ects


75



77



European Regulation

78





framework






Pa

rt I-4

ndash L

ega

l Asp

ects




79

Pa

rt I-4

ndash L

ega

l Asp

ects



3 Categories

80

Open Category


model planes

and UAS

ndash Geofencing

ndash Subcategories

in relation to

potential harm

ndash Exemption for

toys

ndash Control thru

police

Certified Category


UAS gt 25 kg

bull Certification

similar to

manned aviation

bull Pilot licence

(PPL)


Flight Operation

through Certified

Entities

Specific Category

bull Mostly for

commercial

UAS-users


bull Requirements

depend on use

of operation


Flight Operation)


Entitiesldquo

Pa

rt I-4

ndash L

ega

l Asp

ects



81

Pa

rt I-4

ndash L

ega

l Asp

ects



RPAS segments

82








rt I-4

ndash L

ega

l Asp

ects



RPAS segments









years



83

Pa

rt I-4

ndash L

ega

l Asp

ects



camera

37

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs



38

φi

i

Light

source

Observer

North

φr

r

)(

)()(

ii

rriirrii

E

L

BRDF





F

D A A

B

C E G

O

Honkavaara 2014

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs

wwweurosdrnet



Michael Cramer




wwweurosdrnet








Data Acquisition

RPAS Photogrammetry

=




rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts

41





Distance


Base

xlsquo

xlsquolsquo

Accuracy parameters


ndash Base


bull Measurement

accuracy in image

space




quality


sXY

sZ


Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





Distance Z

Base B

xlsquo

xlsquolsquo

sXY

sZ

43

x X y Y

c Z c Z

x X B y Y

c Z c Z

x

c B c BZ

x x p

y yY Z Z

c c

xX Z

c


Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





Distance Z

Base B

xlsquo

xlsquolsquo



Z b x

Y X b x

Zm

B

m

s s

s s s

sXY

sZ

2

Z Z

x Z b Z

Z B

Zm

c

s s

s s s

Accuracy

44


Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



photogrammetry




xlsquo

xlsquolsquo




sXY

sZ



(analog) airborne






projects

45

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





bull Image scale



XYZ b xq ms s

Z b x

Y X b x

Zm

m

Bs s

s s s


46

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts






11 21 31

13 23 33

12 22 32

13 23 33

r X r Y r Zx z

r X r Y r Z

r X r Y r Zy z

r X r Y r Z

0

0

0

X X X

Y Y Y

Z Z Z

0

0

0

x x x

y y y

z z z c

with 11 12 13

31 32 33

r x r y r zX Z

r x r y r z

21 22 23

31 32 33

r x r y r cY Z

r x r y r c


coordinate frames



coordinates





47

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



0

0

0

X X X

Y Y Y

Z Z Z

0

0

0

x x x

y y y

z z z c


11 21 31

13 23 33

12 22 32

13 23 33

r X r Y r Zx z x

r X r Y r Z

r X r Y r Zy z y

r X r Y r Z









with

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


Camera Calibration





49

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Object coordinate

system

camera

P object point

Plsquo image point


cx

cz

cy

0X

X

)( Rp

p



X

Y

Z

0

l l l Cam

Cam X X R p

50

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




Unit cx

cz

cy

X

Y

Z

bzby

bx


0X

X

)( Rp

p

0

bX

GPS

bX

Cam

bX

e



Object coordinate

system

camera

P object point

Plsquo image point


51

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





Keep in mind





0 l l Cab b b

Ca

m


b b

Cam GPS X X

( )b

Cam R

( ) ( )l n

b b R R

52

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




close-range

53

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Standard-AT

GNSS supported AT

few control points

Calibrated cams +

self-calibration

(math models)

GNSSinertial data



FBMLSM)

RPAS

Few control points

Full in-situ camera

calibration

(physical models

GNSS (code)



(SIFT key points)

camera calibration


up of Image Block


block

Product generation

DTMDSM (Dense

Matching) amp Ortho

Transformation into


Process chain

54

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts










image




55

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




56





x1j

x2j

x3j

Xj

P1

P2

P3

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




copy R Fergus 2014

Incremental SfM

58

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Algorithm






(DLT)



60

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


ca

me

ras

points

61


Algorithm







calibration


new 3D points



triangulation


bundle adjustment

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


ca

me

ras

points

62


Algorithm







calibration


new 3D points



triangulation


bundle adjustment

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Algorithm


rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


Image Matching













64

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts











65






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


EduServ 12 (2014)


66





Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts

wwweurosdrnet



Legal Aspects



Geoinformatik


wwweurosdrnet









69









for subsequent use



rt I-4

ndash L

ega

l Asp

ects




70





rt I-4

ndash L

ega

l Asp

ects





Privacy


apply




72

Pa

rt I-4

ndash L

ega

l Asp

ects







growing


aviation background


before end 2020


73

Pa

rt I-4

ndash L

ega

l Asp

ects



Germany








(Permit required)




74

Pa

rt I-4

ndash L

ega

l Asp

ects


75



77



European Regulation

78





framework






Pa

rt I-4

ndash L

ega

l Asp

ects




79

Pa

rt I-4

ndash L

ega

l Asp

ects



3 Categories

80

Open Category


model planes

and UAS

ndash Geofencing

ndash Subcategories

in relation to

potential harm

ndash Exemption for

toys

ndash Control thru

police

Certified Category


UAS gt 25 kg

bull Certification

similar to

manned aviation

bull Pilot licence

(PPL)


Flight Operation

through Certified

Entities

Specific Category

bull Mostly for

commercial

UAS-users


bull Requirements

depend on use

of operation


Flight Operation)


Entitiesldquo

Pa

rt I-4

ndash L

ega

l Asp

ects



81

Pa

rt I-4

ndash L

ega

l Asp

ects



RPAS segments

82








rt I-4

ndash L

ega

l Asp

ects



RPAS segments









years



83

Pa

rt I-4

ndash L

ega

l Asp

ects



38

φi

i

Light

source

Observer

North

φr

r

)(

)()(

ii

rriirrii

E

L

BRDF





F

D A A

B

C E G

O

Honkavaara 2014

Pa

rt I-2

ndash S

yste

ms amp

Se

nso

rs

wwweurosdrnet



Michael Cramer




wwweurosdrnet








Data Acquisition

RPAS Photogrammetry

=




rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts

41





Distance


Base

xlsquo

xlsquolsquo

Accuracy parameters


ndash Base


bull Measurement

accuracy in image

space




quality


sXY

sZ


Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





Distance Z

Base B

xlsquo

xlsquolsquo

sXY

sZ

43

x X y Y

c Z c Z

x X B y Y

c Z c Z

x

c B c BZ

x x p

y yY Z Z

c c

xX Z

c


Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





Distance Z

Base B

xlsquo

xlsquolsquo



Z b x

Y X b x

Zm

B

m

s s

s s s

sXY

sZ

2

Z Z

x Z b Z

Z B

Zm

c

s s

s s s

Accuracy

44


Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



photogrammetry




xlsquo

xlsquolsquo




sXY

sZ



(analog) airborne






projects

45

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





bull Image scale



XYZ b xq ms s

Z b x

Y X b x

Zm

m

Bs s

s s s


46

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts






11 21 31

13 23 33

12 22 32

13 23 33

r X r Y r Zx z

r X r Y r Z

r X r Y r Zy z

r X r Y r Z

0

0

0

X X X

Y Y Y

Z Z Z

0

0

0

x x x

y y y

z z z c

with 11 12 13

31 32 33

r x r y r zX Z

r x r y r z

21 22 23

31 32 33

r x r y r cY Z

r x r y r c


coordinate frames



coordinates





47

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



0

0

0

X X X

Y Y Y

Z Z Z

0

0

0

x x x

y y y

z z z c


11 21 31

13 23 33

12 22 32

13 23 33

r X r Y r Zx z x

r X r Y r Z

r X r Y r Zy z y

r X r Y r Z









with

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


Camera Calibration





49

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Object coordinate

system

camera

P object point

Plsquo image point


cx

cz

cy

0X

X

)( Rp

p



X

Y

Z

0

l l l Cam

Cam X X R p

50

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




Unit cx

cz

cy

X

Y

Z

bzby

bx


0X

X

)( Rp

p

0

bX

GPS

bX

Cam

bX

e



Object coordinate

system

camera

P object point

Plsquo image point


51

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





Keep in mind





0 l l Cab b b

Ca

m


b b

Cam GPS X X

( )b

Cam R

( ) ( )l n

b b R R

52

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




close-range

53

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Standard-AT

GNSS supported AT

few control points

Calibrated cams +

self-calibration

(math models)

GNSSinertial data



FBMLSM)

RPAS

Few control points

Full in-situ camera

calibration

(physical models

GNSS (code)



(SIFT key points)

camera calibration


up of Image Block


block

Product generation

DTMDSM (Dense

Matching) amp Ortho

Transformation into


Process chain

54

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts










image




55

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




56





x1j

x2j

x3j

Xj

P1

P2

P3

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




copy R Fergus 2014

Incremental SfM

58

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Algorithm






(DLT)



60

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


ca

me

ras

points

61


Algorithm







calibration


new 3D points



triangulation


bundle adjustment

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


ca

me

ras

points

62


Algorithm







calibration


new 3D points



triangulation


bundle adjustment

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Algorithm


rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


Image Matching













64

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts











65






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


EduServ 12 (2014)


66





Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts

wwweurosdrnet



Legal Aspects



Geoinformatik


wwweurosdrnet









69









for subsequent use



rt I-4

ndash L

ega

l Asp

ects




70





rt I-4

ndash L

ega

l Asp

ects





Privacy


apply




72

Pa

rt I-4

ndash L

ega

l Asp

ects







growing


aviation background


before end 2020


73

Pa

rt I-4

ndash L

ega

l Asp

ects



Germany








(Permit required)




74

Pa

rt I-4

ndash L

ega

l Asp

ects


75



77



European Regulation

78





framework






Pa

rt I-4

ndash L

ega

l Asp

ects




79

Pa

rt I-4

ndash L

ega

l Asp

ects



3 Categories

80

Open Category


model planes

and UAS

ndash Geofencing

ndash Subcategories

in relation to

potential harm

ndash Exemption for

toys

ndash Control thru

police

Certified Category


UAS gt 25 kg

bull Certification

similar to

manned aviation

bull Pilot licence

(PPL)


Flight Operation

through Certified

Entities

Specific Category

bull Mostly for

commercial

UAS-users


bull Requirements

depend on use

of operation


Flight Operation)


Entitiesldquo

Pa

rt I-4

ndash L

ega

l Asp

ects



81

Pa

rt I-4

ndash L

ega

l Asp

ects



RPAS segments

82








rt I-4

ndash L

ega

l Asp

ects



RPAS segments









years



83

Pa

rt I-4

ndash L

ega

l Asp

ects

wwweurosdrnet



Michael Cramer




wwweurosdrnet








Data Acquisition

RPAS Photogrammetry

=




rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts

41





Distance


Base

xlsquo

xlsquolsquo

Accuracy parameters


ndash Base


bull Measurement

accuracy in image

space




quality


sXY

sZ


Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





Distance Z

Base B

xlsquo

xlsquolsquo

sXY

sZ

43

x X y Y

c Z c Z

x X B y Y

c Z c Z

x

c B c BZ

x x p

y yY Z Z

c c

xX Z

c


Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





Distance Z

Base B

xlsquo

xlsquolsquo



Z b x

Y X b x

Zm

B

m

s s

s s s

sXY

sZ

2

Z Z

x Z b Z

Z B

Zm

c

s s

s s s

Accuracy

44


Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



photogrammetry




xlsquo

xlsquolsquo




sXY

sZ



(analog) airborne






projects

45

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





bull Image scale



XYZ b xq ms s

Z b x

Y X b x

Zm

m

Bs s

s s s


46

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts






11 21 31

13 23 33

12 22 32

13 23 33

r X r Y r Zx z

r X r Y r Z

r X r Y r Zy z

r X r Y r Z

0

0

0

X X X

Y Y Y

Z Z Z

0

0

0

x x x

y y y

z z z c

with 11 12 13

31 32 33

r x r y r zX Z

r x r y r z

21 22 23

31 32 33

r x r y r cY Z

r x r y r c


coordinate frames



coordinates





47

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



0

0

0

X X X

Y Y Y

Z Z Z

0

0

0

x x x

y y y

z z z c


11 21 31

13 23 33

12 22 32

13 23 33

r X r Y r Zx z x

r X r Y r Z

r X r Y r Zy z y

r X r Y r Z









with

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


Camera Calibration





49

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Object coordinate

system

camera

P object point

Plsquo image point


cx

cz

cy

0X

X

)( Rp

p



X

Y

Z

0

l l l Cam

Cam X X R p

50

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




Unit cx

cz

cy

X

Y

Z

bzby

bx


0X

X

)( Rp

p

0

bX

GPS

bX

Cam

bX

e



Object coordinate

system

camera

P object point

Plsquo image point


51

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





Keep in mind





0 l l Cab b b

Ca

m


b b

Cam GPS X X

( )b

Cam R

( ) ( )l n

b b R R

52

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




close-range

53

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Standard-AT

GNSS supported AT

few control points

Calibrated cams +

self-calibration

(math models)

GNSSinertial data



FBMLSM)

RPAS

Few control points

Full in-situ camera

calibration

(physical models

GNSS (code)



(SIFT key points)

camera calibration


up of Image Block


block

Product generation

DTMDSM (Dense

Matching) amp Ortho

Transformation into


Process chain

54

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts










image




55

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




56





x1j

x2j

x3j

Xj

P1

P2

P3

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




copy R Fergus 2014

Incremental SfM

58

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Algorithm






(DLT)



60

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


ca

me

ras

points

61


Algorithm







calibration


new 3D points



triangulation


bundle adjustment

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


ca

me

ras

points

62


Algorithm







calibration


new 3D points



triangulation


bundle adjustment

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Algorithm


rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


Image Matching













64

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts











65






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


EduServ 12 (2014)


66





Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts

wwweurosdrnet



Legal Aspects



Geoinformatik


wwweurosdrnet









69









for subsequent use



rt I-4

ndash L

ega

l Asp

ects




70





rt I-4

ndash L

ega

l Asp

ects





Privacy


apply




72

Pa

rt I-4

ndash L

ega

l Asp

ects







growing


aviation background


before end 2020


73

Pa

rt I-4

ndash L

ega

l Asp

ects



Germany








(Permit required)




74

Pa

rt I-4

ndash L

ega

l Asp

ects


75



77



European Regulation

78





framework






Pa

rt I-4

ndash L

ega

l Asp

ects




79

Pa

rt I-4

ndash L

ega

l Asp

ects



3 Categories

80

Open Category


model planes

and UAS

ndash Geofencing

ndash Subcategories

in relation to

potential harm

ndash Exemption for

toys

ndash Control thru

police

Certified Category


UAS gt 25 kg

bull Certification

similar to

manned aviation

bull Pilot licence

(PPL)


Flight Operation

through Certified

Entities

Specific Category

bull Mostly for

commercial

UAS-users


bull Requirements

depend on use

of operation


Flight Operation)


Entitiesldquo

Pa

rt I-4

ndash L

ega

l Asp

ects



81

Pa

rt I-4

ndash L

ega

l Asp

ects



RPAS segments

82








rt I-4

ndash L

ega

l Asp

ects



RPAS segments









years



83

Pa

rt I-4

ndash L

ega

l Asp

ects

wwweurosdrnet








Data Acquisition

RPAS Photogrammetry

=




rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts

41





Distance


Base

xlsquo

xlsquolsquo

Accuracy parameters


ndash Base


bull Measurement

accuracy in image

space




quality


sXY

sZ


Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





Distance Z

Base B

xlsquo

xlsquolsquo

sXY

sZ

43

x X y Y

c Z c Z

x X B y Y

c Z c Z

x

c B c BZ

x x p

y yY Z Z

c c

xX Z

c


Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





Distance Z

Base B

xlsquo

xlsquolsquo



Z b x

Y X b x

Zm

B

m

s s

s s s

sXY

sZ

2

Z Z

x Z b Z

Z B

Zm

c

s s

s s s

Accuracy

44


Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



photogrammetry




xlsquo

xlsquolsquo




sXY

sZ



(analog) airborne






projects

45

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





bull Image scale



XYZ b xq ms s

Z b x

Y X b x

Zm

m

Bs s

s s s


46

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts






11 21 31

13 23 33

12 22 32

13 23 33

r X r Y r Zx z

r X r Y r Z

r X r Y r Zy z

r X r Y r Z

0

0

0

X X X

Y Y Y

Z Z Z

0

0

0

x x x

y y y

z z z c

with 11 12 13

31 32 33

r x r y r zX Z

r x r y r z

21 22 23

31 32 33

r x r y r cY Z

r x r y r c


coordinate frames



coordinates





47

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



0

0

0

X X X

Y Y Y

Z Z Z

0

0

0

x x x

y y y

z z z c


11 21 31

13 23 33

12 22 32

13 23 33

r X r Y r Zx z x

r X r Y r Z

r X r Y r Zy z y

r X r Y r Z









with

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


Camera Calibration





49

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Object coordinate

system

camera

P object point

Plsquo image point


cx

cz

cy

0X

X

)( Rp

p



X

Y

Z

0

l l l Cam

Cam X X R p

50

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




Unit cx

cz

cy

X

Y

Z

bzby

bx


0X

X

)( Rp

p

0

bX

GPS

bX

Cam

bX

e



Object coordinate

system

camera

P object point

Plsquo image point


51

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





Keep in mind





0 l l Cab b b

Ca

m


b b

Cam GPS X X

( )b

Cam R

( ) ( )l n

b b R R

52

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




close-range

53

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Standard-AT

GNSS supported AT

few control points

Calibrated cams +

self-calibration

(math models)

GNSSinertial data



FBMLSM)

RPAS

Few control points

Full in-situ camera

calibration

(physical models

GNSS (code)



(SIFT key points)

camera calibration


up of Image Block


block

Product generation

DTMDSM (Dense

Matching) amp Ortho

Transformation into


Process chain

54

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts










image




55

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




56





x1j

x2j

x3j

Xj

P1

P2

P3

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




copy R Fergus 2014

Incremental SfM

58

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Algorithm






(DLT)



60

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


ca

me

ras

points

61


Algorithm







calibration


new 3D points



triangulation


bundle adjustment

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


ca

me

ras

points

62


Algorithm







calibration


new 3D points



triangulation


bundle adjustment

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Algorithm


rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


Image Matching













64

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts











65






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


EduServ 12 (2014)


66





Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts

wwweurosdrnet



Legal Aspects



Geoinformatik


wwweurosdrnet









69









for subsequent use



rt I-4

ndash L

ega

l Asp

ects




70





rt I-4

ndash L

ega

l Asp

ects





Privacy


apply




72

Pa

rt I-4

ndash L

ega

l Asp

ects







growing


aviation background


before end 2020


73

Pa

rt I-4

ndash L

ega

l Asp

ects



Germany








(Permit required)




74

Pa

rt I-4

ndash L

ega

l Asp

ects


75



77



European Regulation

78





framework






Pa

rt I-4

ndash L

ega

l Asp

ects




79

Pa

rt I-4

ndash L

ega

l Asp

ects



3 Categories

80

Open Category


model planes

and UAS

ndash Geofencing

ndash Subcategories

in relation to

potential harm

ndash Exemption for

toys

ndash Control thru

police

Certified Category


UAS gt 25 kg

bull Certification

similar to

manned aviation

bull Pilot licence

(PPL)


Flight Operation

through Certified

Entities

Specific Category

bull Mostly for

commercial

UAS-users


bull Requirements

depend on use

of operation


Flight Operation)


Entitiesldquo

Pa

rt I-4

ndash L

ega

l Asp

ects



81

Pa

rt I-4

ndash L

ega

l Asp

ects



RPAS segments

82








rt I-4

ndash L

ega

l Asp

ects



RPAS segments









years



83

Pa

rt I-4

ndash L

ega

l Asp

ects


Data Acquisition

RPAS Photogrammetry

=




rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts

41





Distance


Base

xlsquo

xlsquolsquo

Accuracy parameters


ndash Base


bull Measurement

accuracy in image

space




quality


sXY

sZ


Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





Distance Z

Base B

xlsquo

xlsquolsquo

sXY

sZ

43

x X y Y

c Z c Z

x X B y Y

c Z c Z

x

c B c BZ

x x p

y yY Z Z

c c

xX Z

c


Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





Distance Z

Base B

xlsquo

xlsquolsquo



Z b x

Y X b x

Zm

B

m

s s

s s s

sXY

sZ

2

Z Z

x Z b Z

Z B

Zm

c

s s

s s s

Accuracy

44


Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



photogrammetry




xlsquo

xlsquolsquo




sXY

sZ



(analog) airborne






projects

45

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





bull Image scale



XYZ b xq ms s

Z b x

Y X b x

Zm

m

Bs s

s s s


46

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts






11 21 31

13 23 33

12 22 32

13 23 33

r X r Y r Zx z

r X r Y r Z

r X r Y r Zy z

r X r Y r Z

0

0

0

X X X

Y Y Y

Z Z Z

0

0

0

x x x

y y y

z z z c

with 11 12 13

31 32 33

r x r y r zX Z

r x r y r z

21 22 23

31 32 33

r x r y r cY Z

r x r y r c


coordinate frames



coordinates





47

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



0

0

0

X X X

Y Y Y

Z Z Z

0

0

0

x x x

y y y

z z z c


11 21 31

13 23 33

12 22 32

13 23 33

r X r Y r Zx z x

r X r Y r Z

r X r Y r Zy z y

r X r Y r Z









with

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


Camera Calibration





49

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Object coordinate

system

camera

P object point

Plsquo image point


cx

cz

cy

0X

X

)( Rp

p



X

Y

Z

0

l l l Cam

Cam X X R p

50

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




Unit cx

cz

cy

X

Y

Z

bzby

bx


0X

X

)( Rp

p

0

bX

GPS

bX

Cam

bX

e



Object coordinate

system

camera

P object point

Plsquo image point


51

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





Keep in mind





0 l l Cab b b

Ca

m


b b

Cam GPS X X

( )b

Cam R

( ) ( )l n

b b R R

52

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




close-range

53

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Standard-AT

GNSS supported AT

few control points

Calibrated cams +

self-calibration

(math models)

GNSSinertial data



FBMLSM)

RPAS

Few control points

Full in-situ camera

calibration

(physical models

GNSS (code)



(SIFT key points)

camera calibration


up of Image Block


block

Product generation

DTMDSM (Dense

Matching) amp Ortho

Transformation into


Process chain

54

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts










image




55

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




56





x1j

x2j

x3j

Xj

P1

P2

P3

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




copy R Fergus 2014

Incremental SfM

58

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Algorithm






(DLT)



60

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


ca

me

ras

points

61


Algorithm







calibration


new 3D points



triangulation


bundle adjustment

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


ca

me

ras

points

62


Algorithm







calibration


new 3D points



triangulation


bundle adjustment

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Algorithm


rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


Image Matching













64

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts











65






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


EduServ 12 (2014)


66





Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts

wwweurosdrnet



Legal Aspects



Geoinformatik


wwweurosdrnet









69









for subsequent use



rt I-4

ndash L

ega

l Asp

ects




70





rt I-4

ndash L

ega

l Asp

ects





Privacy


apply




72

Pa

rt I-4

ndash L

ega

l Asp

ects







growing


aviation background


before end 2020


73

Pa

rt I-4

ndash L

ega

l Asp

ects



Germany








(Permit required)




74

Pa

rt I-4

ndash L

ega

l Asp

ects


75



77



European Regulation

78





framework






Pa

rt I-4

ndash L

ega

l Asp

ects




79

Pa

rt I-4

ndash L

ega

l Asp

ects



3 Categories

80

Open Category


model planes

and UAS

ndash Geofencing

ndash Subcategories

in relation to

potential harm

ndash Exemption for

toys

ndash Control thru

police

Certified Category


UAS gt 25 kg

bull Certification

similar to

manned aviation

bull Pilot licence

(PPL)


Flight Operation

through Certified

Entities

Specific Category

bull Mostly for

commercial

UAS-users


bull Requirements

depend on use

of operation


Flight Operation)


Entitiesldquo

Pa

rt I-4

ndash L

ega

l Asp

ects



81

Pa

rt I-4

ndash L

ega

l Asp

ects



RPAS segments

82








rt I-4

ndash L

ega

l Asp

ects



RPAS segments









years



83

Pa

rt I-4

ndash L

ega

l Asp

ects





Distance


Base

xlsquo

xlsquolsquo

Accuracy parameters


ndash Base


bull Measurement

accuracy in image

space




quality


sXY

sZ


Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





Distance Z

Base B

xlsquo

xlsquolsquo

sXY

sZ

43

x X y Y

c Z c Z

x X B y Y

c Z c Z

x

c B c BZ

x x p

y yY Z Z

c c

xX Z

c


Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





Distance Z

Base B

xlsquo

xlsquolsquo



Z b x

Y X b x

Zm

B

m

s s

s s s

sXY

sZ

2

Z Z

x Z b Z

Z B

Zm

c

s s

s s s

Accuracy

44


Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



photogrammetry




xlsquo

xlsquolsquo




sXY

sZ



(analog) airborne






projects

45

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





bull Image scale



XYZ b xq ms s

Z b x

Y X b x

Zm

m

Bs s

s s s


46

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts






11 21 31

13 23 33

12 22 32

13 23 33

r X r Y r Zx z

r X r Y r Z

r X r Y r Zy z

r X r Y r Z

0

0

0

X X X

Y Y Y

Z Z Z

0

0

0

x x x

y y y

z z z c

with 11 12 13

31 32 33

r x r y r zX Z

r x r y r z

21 22 23

31 32 33

r x r y r cY Z

r x r y r c


coordinate frames



coordinates





47

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



0

0

0

X X X

Y Y Y

Z Z Z

0

0

0

x x x

y y y

z z z c


11 21 31

13 23 33

12 22 32

13 23 33

r X r Y r Zx z x

r X r Y r Z

r X r Y r Zy z y

r X r Y r Z









with

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


Camera Calibration





49

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Object coordinate

system

camera

P object point

Plsquo image point


cx

cz

cy

0X

X

)( Rp

p



X

Y

Z

0

l l l Cam

Cam X X R p

50

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




Unit cx

cz

cy

X

Y

Z

bzby

bx


0X

X

)( Rp

p

0

bX

GPS

bX

Cam

bX

e



Object coordinate

system

camera

P object point

Plsquo image point


51

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





Keep in mind





0 l l Cab b b

Ca

m


b b

Cam GPS X X

( )b

Cam R

( ) ( )l n

b b R R

52

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




close-range

53

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Standard-AT

GNSS supported AT

few control points

Calibrated cams +

self-calibration

(math models)

GNSSinertial data



FBMLSM)

RPAS

Few control points

Full in-situ camera

calibration

(physical models

GNSS (code)



(SIFT key points)

camera calibration


up of Image Block


block

Product generation

DTMDSM (Dense

Matching) amp Ortho

Transformation into


Process chain

54

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts










image




55

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




56





x1j

x2j

x3j

Xj

P1

P2

P3

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




copy R Fergus 2014

Incremental SfM

58

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Algorithm






(DLT)



60

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


ca

me

ras

points

61


Algorithm







calibration


new 3D points



triangulation


bundle adjustment

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


ca

me

ras

points

62


Algorithm







calibration


new 3D points



triangulation


bundle adjustment

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Algorithm


rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


Image Matching













64

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts











65






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


EduServ 12 (2014)


66





Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts

wwweurosdrnet



Legal Aspects



Geoinformatik


wwweurosdrnet









69









for subsequent use



rt I-4

ndash L

ega

l Asp

ects




70





rt I-4

ndash L

ega

l Asp

ects





Privacy


apply




72

Pa

rt I-4

ndash L

ega

l Asp

ects







growing


aviation background


before end 2020


73

Pa

rt I-4

ndash L

ega

l Asp

ects



Germany








(Permit required)




74

Pa

rt I-4

ndash L

ega

l Asp

ects


75



77



European Regulation

78





framework






Pa

rt I-4

ndash L

ega

l Asp

ects




79

Pa

rt I-4

ndash L

ega

l Asp

ects



3 Categories

80

Open Category


model planes

and UAS

ndash Geofencing

ndash Subcategories

in relation to

potential harm

ndash Exemption for

toys

ndash Control thru

police

Certified Category


UAS gt 25 kg

bull Certification

similar to

manned aviation

bull Pilot licence

(PPL)


Flight Operation

through Certified

Entities

Specific Category

bull Mostly for

commercial

UAS-users


bull Requirements

depend on use

of operation


Flight Operation)


Entitiesldquo

Pa

rt I-4

ndash L

ega

l Asp

ects



81

Pa

rt I-4

ndash L

ega

l Asp

ects



RPAS segments

82








rt I-4

ndash L

ega

l Asp

ects



RPAS segments









years



83

Pa

rt I-4

ndash L

ega

l Asp

ects





Distance Z

Base B

xlsquo

xlsquolsquo

sXY

sZ

43

x X y Y

c Z c Z

x X B y Y

c Z c Z

x

c B c BZ

x x p

y yY Z Z

c c

xX Z

c


Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





Distance Z

Base B

xlsquo

xlsquolsquo



Z b x

Y X b x

Zm

B

m

s s

s s s

sXY

sZ

2

Z Z

x Z b Z

Z B

Zm

c

s s

s s s

Accuracy

44


Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



photogrammetry




xlsquo

xlsquolsquo




sXY

sZ



(analog) airborne






projects

45

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





bull Image scale



XYZ b xq ms s

Z b x

Y X b x

Zm

m

Bs s

s s s


46

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts






11 21 31

13 23 33

12 22 32

13 23 33

r X r Y r Zx z

r X r Y r Z

r X r Y r Zy z

r X r Y r Z

0

0

0

X X X

Y Y Y

Z Z Z

0

0

0

x x x

y y y

z z z c

with 11 12 13

31 32 33

r x r y r zX Z

r x r y r z

21 22 23

31 32 33

r x r y r cY Z

r x r y r c


coordinate frames



coordinates





47

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



0

0

0

X X X

Y Y Y

Z Z Z

0

0

0

x x x

y y y

z z z c


11 21 31

13 23 33

12 22 32

13 23 33

r X r Y r Zx z x

r X r Y r Z

r X r Y r Zy z y

r X r Y r Z









with

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


Camera Calibration





49

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Object coordinate

system

camera

P object point

Plsquo image point


cx

cz

cy

0X

X

)( Rp

p



X

Y

Z

0

l l l Cam

Cam X X R p

50

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




Unit cx

cz

cy

X

Y

Z

bzby

bx


0X

X

)( Rp

p

0

bX

GPS

bX

Cam

bX

e



Object coordinate

system

camera

P object point

Plsquo image point


51

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





Keep in mind





0 l l Cab b b

Ca

m


b b

Cam GPS X X

( )b

Cam R

( ) ( )l n

b b R R

52

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




close-range

53

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Standard-AT

GNSS supported AT

few control points

Calibrated cams +

self-calibration

(math models)

GNSSinertial data



FBMLSM)

RPAS

Few control points

Full in-situ camera

calibration

(physical models

GNSS (code)



(SIFT key points)

camera calibration


up of Image Block


block

Product generation

DTMDSM (Dense

Matching) amp Ortho

Transformation into


Process chain

54

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts










image




55

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




56





x1j

x2j

x3j

Xj

P1

P2

P3

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




copy R Fergus 2014

Incremental SfM

58

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Algorithm






(DLT)



60

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


ca

me

ras

points

61


Algorithm







calibration


new 3D points



triangulation


bundle adjustment

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


ca

me

ras

points

62


Algorithm







calibration


new 3D points



triangulation


bundle adjustment

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Algorithm


rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


Image Matching













64

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts











65






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


EduServ 12 (2014)


66





Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts

wwweurosdrnet



Legal Aspects



Geoinformatik


wwweurosdrnet









69









for subsequent use



rt I-4

ndash L

ega

l Asp

ects




70





rt I-4

ndash L

ega

l Asp

ects





Privacy


apply




72

Pa

rt I-4

ndash L

ega

l Asp

ects







growing


aviation background


before end 2020


73

Pa

rt I-4

ndash L

ega

l Asp

ects



Germany








(Permit required)




74

Pa

rt I-4

ndash L

ega

l Asp

ects


75



77



European Regulation

78





framework






Pa

rt I-4

ndash L

ega

l Asp

ects




79

Pa

rt I-4

ndash L

ega

l Asp

ects



3 Categories

80

Open Category


model planes

and UAS

ndash Geofencing

ndash Subcategories

in relation to

potential harm

ndash Exemption for

toys

ndash Control thru

police

Certified Category


UAS gt 25 kg

bull Certification

similar to

manned aviation

bull Pilot licence

(PPL)


Flight Operation

through Certified

Entities

Specific Category

bull Mostly for

commercial

UAS-users


bull Requirements

depend on use

of operation


Flight Operation)


Entitiesldquo

Pa

rt I-4

ndash L

ega

l Asp

ects



81

Pa

rt I-4

ndash L

ega

l Asp

ects



RPAS segments

82








rt I-4

ndash L

ega

l Asp

ects



RPAS segments









years



83

Pa

rt I-4

ndash L

ega

l Asp

ects





Distance Z

Base B

xlsquo

xlsquolsquo



Z b x

Y X b x

Zm

B

m

s s

s s s

sXY

sZ

2

Z Z

x Z b Z

Z B

Zm

c

s s

s s s

Accuracy

44


Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



photogrammetry




xlsquo

xlsquolsquo




sXY

sZ



(analog) airborne






projects

45

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





bull Image scale



XYZ b xq ms s

Z b x

Y X b x

Zm

m

Bs s

s s s


46

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts






11 21 31

13 23 33

12 22 32

13 23 33

r X r Y r Zx z

r X r Y r Z

r X r Y r Zy z

r X r Y r Z

0

0

0

X X X

Y Y Y

Z Z Z

0

0

0

x x x

y y y

z z z c

with 11 12 13

31 32 33

r x r y r zX Z

r x r y r z

21 22 23

31 32 33

r x r y r cY Z

r x r y r c


coordinate frames



coordinates





47

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



0

0

0

X X X

Y Y Y

Z Z Z

0

0

0

x x x

y y y

z z z c


11 21 31

13 23 33

12 22 32

13 23 33

r X r Y r Zx z x

r X r Y r Z

r X r Y r Zy z y

r X r Y r Z









with

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


Camera Calibration





49

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Object coordinate

system

camera

P object point

Plsquo image point


cx

cz

cy

0X

X

)( Rp

p



X

Y

Z

0

l l l Cam

Cam X X R p

50

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




Unit cx

cz

cy

X

Y

Z

bzby

bx


0X

X

)( Rp

p

0

bX

GPS

bX

Cam

bX

e



Object coordinate

system

camera

P object point

Plsquo image point


51

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





Keep in mind





0 l l Cab b b

Ca

m


b b

Cam GPS X X

( )b

Cam R

( ) ( )l n

b b R R

52

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




close-range

53

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Standard-AT

GNSS supported AT

few control points

Calibrated cams +

self-calibration

(math models)

GNSSinertial data



FBMLSM)

RPAS

Few control points

Full in-situ camera

calibration

(physical models

GNSS (code)



(SIFT key points)

camera calibration


up of Image Block


block

Product generation

DTMDSM (Dense

Matching) amp Ortho

Transformation into


Process chain

54

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts










image




55

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




56





x1j

x2j

x3j

Xj

P1

P2

P3

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




copy R Fergus 2014

Incremental SfM

58

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Algorithm






(DLT)



60

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


ca

me

ras

points

61


Algorithm







calibration


new 3D points



triangulation


bundle adjustment

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


ca

me

ras

points

62


Algorithm







calibration


new 3D points



triangulation


bundle adjustment

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Algorithm


rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


Image Matching













64

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts











65






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


EduServ 12 (2014)


66





Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts

wwweurosdrnet



Legal Aspects



Geoinformatik


wwweurosdrnet









69









for subsequent use



rt I-4

ndash L

ega

l Asp

ects




70





rt I-4

ndash L

ega

l Asp

ects





Privacy


apply




72

Pa

rt I-4

ndash L

ega

l Asp

ects







growing


aviation background


before end 2020


73

Pa

rt I-4

ndash L

ega

l Asp

ects



Germany








(Permit required)




74

Pa

rt I-4

ndash L

ega

l Asp

ects


75



77



European Regulation

78





framework






Pa

rt I-4

ndash L

ega

l Asp

ects




79

Pa

rt I-4

ndash L

ega

l Asp

ects



3 Categories

80

Open Category


model planes

and UAS

ndash Geofencing

ndash Subcategories

in relation to

potential harm

ndash Exemption for

toys

ndash Control thru

police

Certified Category


UAS gt 25 kg

bull Certification

similar to

manned aviation

bull Pilot licence

(PPL)


Flight Operation

through Certified

Entities

Specific Category

bull Mostly for

commercial

UAS-users


bull Requirements

depend on use

of operation


Flight Operation)


Entitiesldquo

Pa

rt I-4

ndash L

ega

l Asp

ects



81

Pa

rt I-4

ndash L

ega

l Asp

ects



RPAS segments

82








rt I-4

ndash L

ega

l Asp

ects



RPAS segments









years



83

Pa

rt I-4

ndash L

ega

l Asp

ects



photogrammetry




xlsquo

xlsquolsquo




sXY

sZ



(analog) airborne






projects

45

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





bull Image scale



XYZ b xq ms s

Z b x

Y X b x

Zm

m

Bs s

s s s


46

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts






11 21 31

13 23 33

12 22 32

13 23 33

r X r Y r Zx z

r X r Y r Z

r X r Y r Zy z

r X r Y r Z

0

0

0

X X X

Y Y Y

Z Z Z

0

0

0

x x x

y y y

z z z c

with 11 12 13

31 32 33

r x r y r zX Z

r x r y r z

21 22 23

31 32 33

r x r y r cY Z

r x r y r c


coordinate frames



coordinates





47

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



0

0

0

X X X

Y Y Y

Z Z Z

0

0

0

x x x

y y y

z z z c


11 21 31

13 23 33

12 22 32

13 23 33

r X r Y r Zx z x

r X r Y r Z

r X r Y r Zy z y

r X r Y r Z









with

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


Camera Calibration





49

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Object coordinate

system

camera

P object point

Plsquo image point


cx

cz

cy

0X

X

)( Rp

p



X

Y

Z

0

l l l Cam

Cam X X R p

50

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




Unit cx

cz

cy

X

Y

Z

bzby

bx


0X

X

)( Rp

p

0

bX

GPS

bX

Cam

bX

e



Object coordinate

system

camera

P object point

Plsquo image point


51

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





Keep in mind





0 l l Cab b b

Ca

m


b b

Cam GPS X X

( )b

Cam R

( ) ( )l n

b b R R

52

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




close-range

53

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Standard-AT

GNSS supported AT

few control points

Calibrated cams +

self-calibration

(math models)

GNSSinertial data



FBMLSM)

RPAS

Few control points

Full in-situ camera

calibration

(physical models

GNSS (code)



(SIFT key points)

camera calibration


up of Image Block


block

Product generation

DTMDSM (Dense

Matching) amp Ortho

Transformation into


Process chain

54

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts










image




55

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




56





x1j

x2j

x3j

Xj

P1

P2

P3

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




copy R Fergus 2014

Incremental SfM

58

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Algorithm






(DLT)



60

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


ca

me

ras

points

61


Algorithm







calibration


new 3D points



triangulation


bundle adjustment

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


ca

me

ras

points

62


Algorithm







calibration


new 3D points



triangulation


bundle adjustment

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Algorithm


rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


Image Matching













64

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts











65






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


EduServ 12 (2014)


66





Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts

wwweurosdrnet



Legal Aspects



Geoinformatik


wwweurosdrnet









69









for subsequent use



rt I-4

ndash L

ega

l Asp

ects




70





rt I-4

ndash L

ega

l Asp

ects





Privacy


apply




72

Pa

rt I-4

ndash L

ega

l Asp

ects







growing


aviation background


before end 2020


73

Pa

rt I-4

ndash L

ega

l Asp

ects



Germany








(Permit required)




74

Pa

rt I-4

ndash L

ega

l Asp

ects


75



77



European Regulation

78





framework






Pa

rt I-4

ndash L

ega

l Asp

ects




79

Pa

rt I-4

ndash L

ega

l Asp

ects



3 Categories

80

Open Category


model planes

and UAS

ndash Geofencing

ndash Subcategories

in relation to

potential harm

ndash Exemption for

toys

ndash Control thru

police

Certified Category


UAS gt 25 kg

bull Certification

similar to

manned aviation

bull Pilot licence

(PPL)


Flight Operation

through Certified

Entities

Specific Category

bull Mostly for

commercial

UAS-users


bull Requirements

depend on use

of operation


Flight Operation)


Entitiesldquo

Pa

rt I-4

ndash L

ega

l Asp

ects



81

Pa

rt I-4

ndash L

ega

l Asp

ects



RPAS segments

82








rt I-4

ndash L

ega

l Asp

ects



RPAS segments









years



83

Pa

rt I-4

ndash L

ega

l Asp

ects





bull Image scale



XYZ b xq ms s

Z b x

Y X b x

Zm

m

Bs s

s s s


46

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts






11 21 31

13 23 33

12 22 32

13 23 33

r X r Y r Zx z

r X r Y r Z

r X r Y r Zy z

r X r Y r Z

0

0

0

X X X

Y Y Y

Z Z Z

0

0

0

x x x

y y y

z z z c

with 11 12 13

31 32 33

r x r y r zX Z

r x r y r z

21 22 23

31 32 33

r x r y r cY Z

r x r y r c


coordinate frames



coordinates





47

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



0

0

0

X X X

Y Y Y

Z Z Z

0

0

0

x x x

y y y

z z z c


11 21 31

13 23 33

12 22 32

13 23 33

r X r Y r Zx z x

r X r Y r Z

r X r Y r Zy z y

r X r Y r Z









with

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


Camera Calibration





49

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Object coordinate

system

camera

P object point

Plsquo image point


cx

cz

cy

0X

X

)( Rp

p



X

Y

Z

0

l l l Cam

Cam X X R p

50

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




Unit cx

cz

cy

X

Y

Z

bzby

bx


0X

X

)( Rp

p

0

bX

GPS

bX

Cam

bX

e



Object coordinate

system

camera

P object point

Plsquo image point


51

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





Keep in mind





0 l l Cab b b

Ca

m


b b

Cam GPS X X

( )b

Cam R

( ) ( )l n

b b R R

52

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




close-range

53

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Standard-AT

GNSS supported AT

few control points

Calibrated cams +

self-calibration

(math models)

GNSSinertial data



FBMLSM)

RPAS

Few control points

Full in-situ camera

calibration

(physical models

GNSS (code)



(SIFT key points)

camera calibration


up of Image Block


block

Product generation

DTMDSM (Dense

Matching) amp Ortho

Transformation into


Process chain

54

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts










image




55

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




56





x1j

x2j

x3j

Xj

P1

P2

P3

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




copy R Fergus 2014

Incremental SfM

58

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Algorithm






(DLT)



60

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


ca

me

ras

points

61


Algorithm







calibration


new 3D points



triangulation


bundle adjustment

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


ca

me

ras

points

62


Algorithm







calibration


new 3D points



triangulation


bundle adjustment

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Algorithm


rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


Image Matching













64

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts











65






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


EduServ 12 (2014)


66





Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts

wwweurosdrnet



Legal Aspects



Geoinformatik


wwweurosdrnet









69









for subsequent use



rt I-4

ndash L

ega

l Asp

ects




70





rt I-4

ndash L

ega

l Asp

ects





Privacy


apply




72

Pa

rt I-4

ndash L

ega

l Asp

ects







growing


aviation background


before end 2020


73

Pa

rt I-4

ndash L

ega

l Asp

ects



Germany








(Permit required)




74

Pa

rt I-4

ndash L

ega

l Asp

ects


75



77



European Regulation

78





framework






Pa

rt I-4

ndash L

ega

l Asp

ects




79

Pa

rt I-4

ndash L

ega

l Asp

ects



3 Categories

80

Open Category


model planes

and UAS

ndash Geofencing

ndash Subcategories

in relation to

potential harm

ndash Exemption for

toys

ndash Control thru

police

Certified Category


UAS gt 25 kg

bull Certification

similar to

manned aviation

bull Pilot licence

(PPL)


Flight Operation

through Certified

Entities

Specific Category

bull Mostly for

commercial

UAS-users


bull Requirements

depend on use

of operation


Flight Operation)


Entitiesldquo

Pa

rt I-4

ndash L

ega

l Asp

ects



81

Pa

rt I-4

ndash L

ega

l Asp

ects



RPAS segments

82








rt I-4

ndash L

ega

l Asp

ects



RPAS segments









years



83

Pa

rt I-4

ndash L

ega

l Asp

ects






11 21 31

13 23 33

12 22 32

13 23 33

r X r Y r Zx z

r X r Y r Z

r X r Y r Zy z

r X r Y r Z

0

0

0

X X X

Y Y Y

Z Z Z

0

0

0

x x x

y y y

z z z c

with 11 12 13

31 32 33

r x r y r zX Z

r x r y r z

21 22 23

31 32 33

r x r y r cY Z

r x r y r c


coordinate frames



coordinates





47

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



0

0

0

X X X

Y Y Y

Z Z Z

0

0

0

x x x

y y y

z z z c


11 21 31

13 23 33

12 22 32

13 23 33

r X r Y r Zx z x

r X r Y r Z

r X r Y r Zy z y

r X r Y r Z









with

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


Camera Calibration





49

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Object coordinate

system

camera

P object point

Plsquo image point


cx

cz

cy

0X

X

)( Rp

p



X

Y

Z

0

l l l Cam

Cam X X R p

50

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




Unit cx

cz

cy

X

Y

Z

bzby

bx


0X

X

)( Rp

p

0

bX

GPS

bX

Cam

bX

e



Object coordinate

system

camera

P object point

Plsquo image point


51

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





Keep in mind





0 l l Cab b b

Ca

m


b b

Cam GPS X X

( )b

Cam R

( ) ( )l n

b b R R

52

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




close-range

53

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Standard-AT

GNSS supported AT

few control points

Calibrated cams +

self-calibration

(math models)

GNSSinertial data



FBMLSM)

RPAS

Few control points

Full in-situ camera

calibration

(physical models

GNSS (code)



(SIFT key points)

camera calibration


up of Image Block


block

Product generation

DTMDSM (Dense

Matching) amp Ortho

Transformation into


Process chain

54

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts










image




55

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




56





x1j

x2j

x3j

Xj

P1

P2

P3

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




copy R Fergus 2014

Incremental SfM

58

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Algorithm






(DLT)



60

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


ca

me

ras

points

61


Algorithm







calibration


new 3D points



triangulation


bundle adjustment

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


ca

me

ras

points

62


Algorithm







calibration


new 3D points



triangulation


bundle adjustment

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Algorithm


rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


Image Matching













64

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts











65






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


EduServ 12 (2014)


66





Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts

wwweurosdrnet



Legal Aspects



Geoinformatik


wwweurosdrnet









69









for subsequent use



rt I-4

ndash L

ega

l Asp

ects




70





rt I-4

ndash L

ega

l Asp

ects





Privacy


apply




72

Pa

rt I-4

ndash L

ega

l Asp

ects







growing


aviation background


before end 2020


73

Pa

rt I-4

ndash L

ega

l Asp

ects



Germany








(Permit required)




74

Pa

rt I-4

ndash L

ega

l Asp

ects


75



77



European Regulation

78





framework






Pa

rt I-4

ndash L

ega

l Asp

ects




79

Pa

rt I-4

ndash L

ega

l Asp

ects



3 Categories

80

Open Category


model planes

and UAS

ndash Geofencing

ndash Subcategories

in relation to

potential harm

ndash Exemption for

toys

ndash Control thru

police

Certified Category


UAS gt 25 kg

bull Certification

similar to

manned aviation

bull Pilot licence

(PPL)


Flight Operation

through Certified

Entities

Specific Category

bull Mostly for

commercial

UAS-users


bull Requirements

depend on use

of operation


Flight Operation)


Entitiesldquo

Pa

rt I-4

ndash L

ega

l Asp

ects



81

Pa

rt I-4

ndash L

ega

l Asp

ects



RPAS segments

82








rt I-4

ndash L

ega

l Asp

ects



RPAS segments









years



83

Pa

rt I-4

ndash L

ega

l Asp

ects



0

0

0

X X X

Y Y Y

Z Z Z

0

0

0

x x x

y y y

z z z c


11 21 31

13 23 33

12 22 32

13 23 33

r X r Y r Zx z x

r X r Y r Z

r X r Y r Zy z y

r X r Y r Z









with

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


Camera Calibration





49

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Object coordinate

system

camera

P object point

Plsquo image point


cx

cz

cy

0X

X

)( Rp

p



X

Y

Z

0

l l l Cam

Cam X X R p

50

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




Unit cx

cz

cy

X

Y

Z

bzby

bx


0X

X

)( Rp

p

0

bX

GPS

bX

Cam

bX

e



Object coordinate

system

camera

P object point

Plsquo image point


51

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





Keep in mind





0 l l Cab b b

Ca

m


b b

Cam GPS X X

( )b

Cam R

( ) ( )l n

b b R R

52

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




close-range

53

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Standard-AT

GNSS supported AT

few control points

Calibrated cams +

self-calibration

(math models)

GNSSinertial data



FBMLSM)

RPAS

Few control points

Full in-situ camera

calibration

(physical models

GNSS (code)



(SIFT key points)

camera calibration


up of Image Block


block

Product generation

DTMDSM (Dense

Matching) amp Ortho

Transformation into


Process chain

54

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts










image




55

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




56





x1j

x2j

x3j

Xj

P1

P2

P3

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




copy R Fergus 2014

Incremental SfM

58

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Algorithm






(DLT)



60

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


ca

me

ras

points

61


Algorithm







calibration


new 3D points



triangulation


bundle adjustment

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


ca

me

ras

points

62


Algorithm







calibration


new 3D points



triangulation


bundle adjustment

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Algorithm


rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


Image Matching













64

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts











65






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


EduServ 12 (2014)


66





Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts

wwweurosdrnet



Legal Aspects



Geoinformatik


wwweurosdrnet









69









for subsequent use



rt I-4

ndash L

ega

l Asp

ects




70





rt I-4

ndash L

ega

l Asp

ects





Privacy


apply




72

Pa

rt I-4

ndash L

ega

l Asp

ects







growing


aviation background


before end 2020


73

Pa

rt I-4

ndash L

ega

l Asp

ects



Germany








(Permit required)




74

Pa

rt I-4

ndash L

ega

l Asp

ects


75



77



European Regulation

78





framework






Pa

rt I-4

ndash L

ega

l Asp

ects




79

Pa

rt I-4

ndash L

ega

l Asp

ects



3 Categories

80

Open Category


model planes

and UAS

ndash Geofencing

ndash Subcategories

in relation to

potential harm

ndash Exemption for

toys

ndash Control thru

police

Certified Category


UAS gt 25 kg

bull Certification

similar to

manned aviation

bull Pilot licence

(PPL)


Flight Operation

through Certified

Entities

Specific Category

bull Mostly for

commercial

UAS-users


bull Requirements

depend on use

of operation


Flight Operation)


Entitiesldquo

Pa

rt I-4

ndash L

ega

l Asp

ects



81

Pa

rt I-4

ndash L

ega

l Asp

ects



RPAS segments

82








rt I-4

ndash L

ega

l Asp

ects



RPAS segments









years



83

Pa

rt I-4

ndash L

ega

l Asp

ects


Camera Calibration





49

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Object coordinate

system

camera

P object point

Plsquo image point


cx

cz

cy

0X

X

)( Rp

p



X

Y

Z

0

l l l Cam

Cam X X R p

50

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




Unit cx

cz

cy

X

Y

Z

bzby

bx


0X

X

)( Rp

p

0

bX

GPS

bX

Cam

bX

e



Object coordinate

system

camera

P object point

Plsquo image point


51

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





Keep in mind





0 l l Cab b b

Ca

m


b b

Cam GPS X X

( )b

Cam R

( ) ( )l n

b b R R

52

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




close-range

53

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Standard-AT

GNSS supported AT

few control points

Calibrated cams +

self-calibration

(math models)

GNSSinertial data



FBMLSM)

RPAS

Few control points

Full in-situ camera

calibration

(physical models

GNSS (code)



(SIFT key points)

camera calibration


up of Image Block


block

Product generation

DTMDSM (Dense

Matching) amp Ortho

Transformation into


Process chain

54

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts










image




55

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




56





x1j

x2j

x3j

Xj

P1

P2

P3

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




copy R Fergus 2014

Incremental SfM

58

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Algorithm






(DLT)



60

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


ca

me

ras

points

61


Algorithm







calibration


new 3D points



triangulation


bundle adjustment

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


ca

me

ras

points

62


Algorithm







calibration


new 3D points



triangulation


bundle adjustment

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Algorithm


rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


Image Matching













64

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts











65






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


EduServ 12 (2014)


66





Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts

wwweurosdrnet



Legal Aspects



Geoinformatik


wwweurosdrnet









69









for subsequent use



rt I-4

ndash L

ega

l Asp

ects




70





rt I-4

ndash L

ega

l Asp

ects





Privacy


apply




72

Pa

rt I-4

ndash L

ega

l Asp

ects







growing


aviation background


before end 2020


73

Pa

rt I-4

ndash L

ega

l Asp

ects



Germany








(Permit required)




74

Pa

rt I-4

ndash L

ega

l Asp

ects


75



77



European Regulation

78





framework






Pa

rt I-4

ndash L

ega

l Asp

ects




79

Pa

rt I-4

ndash L

ega

l Asp

ects



3 Categories

80

Open Category


model planes

and UAS

ndash Geofencing

ndash Subcategories

in relation to

potential harm

ndash Exemption for

toys

ndash Control thru

police

Certified Category


UAS gt 25 kg

bull Certification

similar to

manned aviation

bull Pilot licence

(PPL)


Flight Operation

through Certified

Entities

Specific Category

bull Mostly for

commercial

UAS-users


bull Requirements

depend on use

of operation


Flight Operation)


Entitiesldquo

Pa

rt I-4

ndash L

ega

l Asp

ects



81

Pa

rt I-4

ndash L

ega

l Asp

ects



RPAS segments

82








rt I-4

ndash L

ega

l Asp

ects



RPAS segments









years



83

Pa

rt I-4

ndash L

ega

l Asp

ects



Object coordinate

system

camera

P object point

Plsquo image point


cx

cz

cy

0X

X

)( Rp

p



X

Y

Z

0

l l l Cam

Cam X X R p

50

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




Unit cx

cz

cy

X

Y

Z

bzby

bx


0X

X

)( Rp

p

0

bX

GPS

bX

Cam

bX

e



Object coordinate

system

camera

P object point

Plsquo image point


51

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





Keep in mind





0 l l Cab b b

Ca

m


b b

Cam GPS X X

( )b

Cam R

( ) ( )l n

b b R R

52

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




close-range

53

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Standard-AT

GNSS supported AT

few control points

Calibrated cams +

self-calibration

(math models)

GNSSinertial data



FBMLSM)

RPAS

Few control points

Full in-situ camera

calibration

(physical models

GNSS (code)



(SIFT key points)

camera calibration


up of Image Block


block

Product generation

DTMDSM (Dense

Matching) amp Ortho

Transformation into


Process chain

54

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts










image




55

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




56





x1j

x2j

x3j

Xj

P1

P2

P3

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




copy R Fergus 2014

Incremental SfM

58

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Algorithm






(DLT)



60

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


ca

me

ras

points

61


Algorithm







calibration


new 3D points



triangulation


bundle adjustment

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


ca

me

ras

points

62


Algorithm







calibration


new 3D points



triangulation


bundle adjustment

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Algorithm


rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


Image Matching













64

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts











65






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


EduServ 12 (2014)


66





Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts

wwweurosdrnet



Legal Aspects



Geoinformatik


wwweurosdrnet









69









for subsequent use



rt I-4

ndash L

ega

l Asp

ects




70





rt I-4

ndash L

ega

l Asp

ects





Privacy


apply




72

Pa

rt I-4

ndash L

ega

l Asp

ects







growing


aviation background


before end 2020


73

Pa

rt I-4

ndash L

ega

l Asp

ects



Germany








(Permit required)




74

Pa

rt I-4

ndash L

ega

l Asp

ects


75



77



European Regulation

78





framework






Pa

rt I-4

ndash L

ega

l Asp

ects




79

Pa

rt I-4

ndash L

ega

l Asp

ects



3 Categories

80

Open Category


model planes

and UAS

ndash Geofencing

ndash Subcategories

in relation to

potential harm

ndash Exemption for

toys

ndash Control thru

police

Certified Category


UAS gt 25 kg

bull Certification

similar to

manned aviation

bull Pilot licence

(PPL)


Flight Operation

through Certified

Entities

Specific Category

bull Mostly for

commercial

UAS-users


bull Requirements

depend on use

of operation


Flight Operation)


Entitiesldquo

Pa

rt I-4

ndash L

ega

l Asp

ects



81

Pa

rt I-4

ndash L

ega

l Asp

ects



RPAS segments

82








rt I-4

ndash L

ega

l Asp

ects



RPAS segments









years



83

Pa

rt I-4

ndash L

ega

l Asp

ects




Unit cx

cz

cy

X

Y

Z

bzby

bx


0X

X

)( Rp

p

0

bX

GPS

bX

Cam

bX

e



Object coordinate

system

camera

P object point

Plsquo image point


51

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts





Keep in mind





0 l l Cab b b

Ca

m


b b

Cam GPS X X

( )b

Cam R

( ) ( )l n

b b R R

52

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




close-range

53

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Standard-AT

GNSS supported AT

few control points

Calibrated cams +

self-calibration

(math models)

GNSSinertial data



FBMLSM)

RPAS

Few control points

Full in-situ camera

calibration

(physical models

GNSS (code)



(SIFT key points)

camera calibration


up of Image Block


block

Product generation

DTMDSM (Dense

Matching) amp Ortho

Transformation into


Process chain

54

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts










image




55

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




56





x1j

x2j

x3j

Xj

P1

P2

P3

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




copy R Fergus 2014

Incremental SfM

58

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Algorithm






(DLT)



60

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


ca

me

ras

points

61


Algorithm







calibration


new 3D points



triangulation


bundle adjustment

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


ca

me

ras

points

62


Algorithm







calibration


new 3D points



triangulation


bundle adjustment

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Algorithm


rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


Image Matching













64

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts











65






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


EduServ 12 (2014)


66





Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts

wwweurosdrnet



Legal Aspects



Geoinformatik


wwweurosdrnet









69









for subsequent use



rt I-4

ndash L

ega

l Asp

ects




70





rt I-4

ndash L

ega

l Asp

ects





Privacy


apply




72

Pa

rt I-4

ndash L

ega

l Asp

ects







growing


aviation background


before end 2020


73

Pa

rt I-4

ndash L

ega

l Asp

ects



Germany








(Permit required)




74

Pa

rt I-4

ndash L

ega

l Asp

ects


75



77



European Regulation

78





framework






Pa

rt I-4

ndash L

ega

l Asp

ects




79

Pa

rt I-4

ndash L

ega

l Asp

ects



3 Categories

80

Open Category


model planes

and UAS

ndash Geofencing

ndash Subcategories

in relation to

potential harm

ndash Exemption for

toys

ndash Control thru

police

Certified Category


UAS gt 25 kg

bull Certification

similar to

manned aviation

bull Pilot licence

(PPL)


Flight Operation

through Certified

Entities

Specific Category

bull Mostly for

commercial

UAS-users


bull Requirements

depend on use

of operation


Flight Operation)


Entitiesldquo

Pa

rt I-4

ndash L

ega

l Asp

ects



81

Pa

rt I-4

ndash L

ega

l Asp

ects



RPAS segments

82








rt I-4

ndash L

ega

l Asp

ects



RPAS segments









years



83

Pa

rt I-4

ndash L

ega

l Asp

ects





Keep in mind





0 l l Cab b b

Ca

m


b b

Cam GPS X X

( )b

Cam R

( ) ( )l n

b b R R

52

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




close-range

53

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Standard-AT

GNSS supported AT

few control points

Calibrated cams +

self-calibration

(math models)

GNSSinertial data



FBMLSM)

RPAS

Few control points

Full in-situ camera

calibration

(physical models

GNSS (code)



(SIFT key points)

camera calibration


up of Image Block


block

Product generation

DTMDSM (Dense

Matching) amp Ortho

Transformation into


Process chain

54

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts










image




55

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




56





x1j

x2j

x3j

Xj

P1

P2

P3

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




copy R Fergus 2014

Incremental SfM

58

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Algorithm






(DLT)



60

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


ca

me

ras

points

61


Algorithm







calibration


new 3D points



triangulation


bundle adjustment

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


ca

me

ras

points

62


Algorithm







calibration


new 3D points



triangulation


bundle adjustment

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Algorithm


rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


Image Matching













64

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts











65






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


EduServ 12 (2014)


66





Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts

wwweurosdrnet



Legal Aspects



Geoinformatik


wwweurosdrnet









69









for subsequent use



rt I-4

ndash L

ega

l Asp

ects




70





rt I-4

ndash L

ega

l Asp

ects





Privacy


apply




72

Pa

rt I-4

ndash L

ega

l Asp

ects







growing


aviation background


before end 2020


73

Pa

rt I-4

ndash L

ega

l Asp

ects



Germany








(Permit required)




74

Pa

rt I-4

ndash L

ega

l Asp

ects


75



77



European Regulation

78





framework






Pa

rt I-4

ndash L

ega

l Asp

ects




79

Pa

rt I-4

ndash L

ega

l Asp

ects



3 Categories

80

Open Category


model planes

and UAS

ndash Geofencing

ndash Subcategories

in relation to

potential harm

ndash Exemption for

toys

ndash Control thru

police

Certified Category


UAS gt 25 kg

bull Certification

similar to

manned aviation

bull Pilot licence

(PPL)


Flight Operation

through Certified

Entities

Specific Category

bull Mostly for

commercial

UAS-users


bull Requirements

depend on use

of operation


Flight Operation)


Entitiesldquo

Pa

rt I-4

ndash L

ega

l Asp

ects



81

Pa

rt I-4

ndash L

ega

l Asp

ects



RPAS segments

82








rt I-4

ndash L

ega

l Asp

ects



RPAS segments









years



83

Pa

rt I-4

ndash L

ega

l Asp

ects




close-range

53

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Standard-AT

GNSS supported AT

few control points

Calibrated cams +

self-calibration

(math models)

GNSSinertial data



FBMLSM)

RPAS

Few control points

Full in-situ camera

calibration

(physical models

GNSS (code)



(SIFT key points)

camera calibration


up of Image Block


block

Product generation

DTMDSM (Dense

Matching) amp Ortho

Transformation into


Process chain

54

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts










image




55

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




56





x1j

x2j

x3j

Xj

P1

P2

P3

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




copy R Fergus 2014

Incremental SfM

58

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Algorithm






(DLT)



60

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


ca

me

ras

points

61


Algorithm







calibration


new 3D points



triangulation


bundle adjustment

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


ca

me

ras

points

62


Algorithm







calibration


new 3D points



triangulation


bundle adjustment

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Algorithm


rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


Image Matching













64

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts











65






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


EduServ 12 (2014)


66





Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts

wwweurosdrnet



Legal Aspects



Geoinformatik


wwweurosdrnet









69









for subsequent use



rt I-4

ndash L

ega

l Asp

ects




70





rt I-4

ndash L

ega

l Asp

ects





Privacy


apply




72

Pa

rt I-4

ndash L

ega

l Asp

ects







growing


aviation background


before end 2020


73

Pa

rt I-4

ndash L

ega

l Asp

ects



Germany








(Permit required)




74

Pa

rt I-4

ndash L

ega

l Asp

ects


75



77



European Regulation

78





framework






Pa

rt I-4

ndash L

ega

l Asp

ects




79

Pa

rt I-4

ndash L

ega

l Asp

ects



3 Categories

80

Open Category


model planes

and UAS

ndash Geofencing

ndash Subcategories

in relation to

potential harm

ndash Exemption for

toys

ndash Control thru

police

Certified Category


UAS gt 25 kg

bull Certification

similar to

manned aviation

bull Pilot licence

(PPL)


Flight Operation

through Certified

Entities

Specific Category

bull Mostly for

commercial

UAS-users


bull Requirements

depend on use

of operation


Flight Operation)


Entitiesldquo

Pa

rt I-4

ndash L

ega

l Asp

ects



81

Pa

rt I-4

ndash L

ega

l Asp

ects



RPAS segments

82








rt I-4

ndash L

ega

l Asp

ects



RPAS segments









years



83

Pa

rt I-4

ndash L

ega

l Asp

ects



Standard-AT

GNSS supported AT

few control points

Calibrated cams +

self-calibration

(math models)

GNSSinertial data



FBMLSM)

RPAS

Few control points

Full in-situ camera

calibration

(physical models

GNSS (code)



(SIFT key points)

camera calibration


up of Image Block


block

Product generation

DTMDSM (Dense

Matching) amp Ortho

Transformation into


Process chain

54

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts










image




55

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




56





x1j

x2j

x3j

Xj

P1

P2

P3

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




copy R Fergus 2014

Incremental SfM

58

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Algorithm






(DLT)



60

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


ca

me

ras

points

61


Algorithm







calibration


new 3D points



triangulation


bundle adjustment

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


ca

me

ras

points

62


Algorithm







calibration


new 3D points



triangulation


bundle adjustment

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Algorithm


rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


Image Matching













64

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts











65






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


EduServ 12 (2014)


66





Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts

wwweurosdrnet



Legal Aspects



Geoinformatik


wwweurosdrnet









69









for subsequent use



rt I-4

ndash L

ega

l Asp

ects




70





rt I-4

ndash L

ega

l Asp

ects





Privacy


apply




72

Pa

rt I-4

ndash L

ega

l Asp

ects







growing


aviation background


before end 2020


73

Pa

rt I-4

ndash L

ega

l Asp

ects



Germany








(Permit required)




74

Pa

rt I-4

ndash L

ega

l Asp

ects


75



77



European Regulation

78





framework






Pa

rt I-4

ndash L

ega

l Asp

ects




79

Pa

rt I-4

ndash L

ega

l Asp

ects



3 Categories

80

Open Category


model planes

and UAS

ndash Geofencing

ndash Subcategories

in relation to

potential harm

ndash Exemption for

toys

ndash Control thru

police

Certified Category


UAS gt 25 kg

bull Certification

similar to

manned aviation

bull Pilot licence

(PPL)


Flight Operation

through Certified

Entities

Specific Category

bull Mostly for

commercial

UAS-users


bull Requirements

depend on use

of operation


Flight Operation)


Entitiesldquo

Pa

rt I-4

ndash L

ega

l Asp

ects



81

Pa

rt I-4

ndash L

ega

l Asp

ects



RPAS segments

82








rt I-4

ndash L

ega

l Asp

ects



RPAS segments









years



83

Pa

rt I-4

ndash L

ega

l Asp

ects










image




55

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




56





x1j

x2j

x3j

Xj

P1

P2

P3

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




copy R Fergus 2014

Incremental SfM

58

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Algorithm






(DLT)



60

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


ca

me

ras

points

61


Algorithm







calibration


new 3D points



triangulation


bundle adjustment

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


ca

me

ras

points

62


Algorithm







calibration


new 3D points



triangulation


bundle adjustment

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Algorithm


rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


Image Matching













64

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts











65






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


EduServ 12 (2014)


66





Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts

wwweurosdrnet



Legal Aspects



Geoinformatik


wwweurosdrnet









69









for subsequent use



rt I-4

ndash L

ega

l Asp

ects




70





rt I-4

ndash L

ega

l Asp

ects





Privacy


apply




72

Pa

rt I-4

ndash L

ega

l Asp

ects







growing


aviation background


before end 2020


73

Pa

rt I-4

ndash L

ega

l Asp

ects



Germany








(Permit required)




74

Pa

rt I-4

ndash L

ega

l Asp

ects


75



77



European Regulation

78





framework






Pa

rt I-4

ndash L

ega

l Asp

ects




79

Pa

rt I-4

ndash L

ega

l Asp

ects



3 Categories

80

Open Category


model planes

and UAS

ndash Geofencing

ndash Subcategories

in relation to

potential harm

ndash Exemption for

toys

ndash Control thru

police

Certified Category


UAS gt 25 kg

bull Certification

similar to

manned aviation

bull Pilot licence

(PPL)


Flight Operation

through Certified

Entities

Specific Category

bull Mostly for

commercial

UAS-users


bull Requirements

depend on use

of operation


Flight Operation)


Entitiesldquo

Pa

rt I-4

ndash L

ega

l Asp

ects



81

Pa

rt I-4

ndash L

ega

l Asp

ects



RPAS segments

82








rt I-4

ndash L

ega

l Asp

ects



RPAS segments









years



83

Pa

rt I-4

ndash L

ega

l Asp

ects




56





x1j

x2j

x3j

Xj

P1

P2

P3

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




copy R Fergus 2014

Incremental SfM

58

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Algorithm






(DLT)



60

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


ca

me

ras

points

61


Algorithm







calibration


new 3D points



triangulation


bundle adjustment

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


ca

me

ras

points

62


Algorithm







calibration


new 3D points



triangulation


bundle adjustment

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Algorithm


rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


Image Matching













64

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts











65






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


EduServ 12 (2014)


66





Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts

wwweurosdrnet



Legal Aspects



Geoinformatik


wwweurosdrnet









69









for subsequent use



rt I-4

ndash L

ega

l Asp

ects




70





rt I-4

ndash L

ega

l Asp

ects





Privacy


apply




72

Pa

rt I-4

ndash L

ega

l Asp

ects







growing


aviation background


before end 2020


73

Pa

rt I-4

ndash L

ega

l Asp

ects



Germany








(Permit required)




74

Pa

rt I-4

ndash L

ega

l Asp

ects


75



77



European Regulation

78





framework






Pa

rt I-4

ndash L

ega

l Asp

ects




79

Pa

rt I-4

ndash L

ega

l Asp

ects



3 Categories

80

Open Category


model planes

and UAS

ndash Geofencing

ndash Subcategories

in relation to

potential harm

ndash Exemption for

toys

ndash Control thru

police

Certified Category


UAS gt 25 kg

bull Certification

similar to

manned aviation

bull Pilot licence

(PPL)


Flight Operation

through Certified

Entities

Specific Category

bull Mostly for

commercial

UAS-users


bull Requirements

depend on use

of operation


Flight Operation)


Entitiesldquo

Pa

rt I-4

ndash L

ega

l Asp

ects



81

Pa

rt I-4

ndash L

ega

l Asp

ects



RPAS segments

82








rt I-4

ndash L

ega

l Asp

ects



RPAS segments









years



83

Pa

rt I-4

ndash L

ega

l Asp

ects






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts




copy R Fergus 2014

Incremental SfM

58

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Algorithm






(DLT)



60

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


ca

me

ras

points

61


Algorithm







calibration


new 3D points



triangulation


bundle adjustment

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


ca

me

ras

points

62


Algorithm







calibration


new 3D points



triangulation


bundle adjustment

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Algorithm


rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


Image Matching













64

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts











65






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


EduServ 12 (2014)


66





Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts

wwweurosdrnet



Legal Aspects



Geoinformatik


wwweurosdrnet









69









for subsequent use



rt I-4

ndash L

ega

l Asp

ects




70





rt I-4

ndash L

ega

l Asp

ects





Privacy


apply




72

Pa

rt I-4

ndash L

ega

l Asp

ects







growing


aviation background


before end 2020


73

Pa

rt I-4

ndash L

ega

l Asp

ects



Germany








(Permit required)




74

Pa

rt I-4

ndash L

ega

l Asp

ects


75



77



European Regulation

78





framework






Pa

rt I-4

ndash L

ega

l Asp

ects




79

Pa

rt I-4

ndash L

ega

l Asp

ects



3 Categories

80

Open Category


model planes

and UAS

ndash Geofencing

ndash Subcategories

in relation to

potential harm

ndash Exemption for

toys

ndash Control thru

police

Certified Category


UAS gt 25 kg

bull Certification

similar to

manned aviation

bull Pilot licence

(PPL)


Flight Operation

through Certified

Entities

Specific Category

bull Mostly for

commercial

UAS-users


bull Requirements

depend on use

of operation


Flight Operation)


Entitiesldquo

Pa

rt I-4

ndash L

ega

l Asp

ects



81

Pa

rt I-4

ndash L

ega

l Asp

ects



RPAS segments

82








rt I-4

ndash L

ega

l Asp

ects



RPAS segments









years



83

Pa

rt I-4

ndash L

ega

l Asp

ects




copy R Fergus 2014

Incremental SfM

58

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Algorithm






(DLT)



60

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


ca

me

ras

points

61


Algorithm







calibration


new 3D points



triangulation


bundle adjustment

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


ca

me

ras

points

62


Algorithm







calibration


new 3D points



triangulation


bundle adjustment

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Algorithm


rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


Image Matching













64

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts











65






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


EduServ 12 (2014)


66





Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts

wwweurosdrnet



Legal Aspects



Geoinformatik


wwweurosdrnet









69









for subsequent use



rt I-4

ndash L

ega

l Asp

ects




70





rt I-4

ndash L

ega

l Asp

ects





Privacy


apply




72

Pa

rt I-4

ndash L

ega

l Asp

ects







growing


aviation background


before end 2020


73

Pa

rt I-4

ndash L

ega

l Asp

ects



Germany








(Permit required)




74

Pa

rt I-4

ndash L

ega

l Asp

ects


75



77



European Regulation

78





framework






Pa

rt I-4

ndash L

ega

l Asp

ects




79

Pa

rt I-4

ndash L

ega

l Asp

ects



3 Categories

80

Open Category


model planes

and UAS

ndash Geofencing

ndash Subcategories

in relation to

potential harm

ndash Exemption for

toys

ndash Control thru

police

Certified Category


UAS gt 25 kg

bull Certification

similar to

manned aviation

bull Pilot licence

(PPL)


Flight Operation

through Certified

Entities

Specific Category

bull Mostly for

commercial

UAS-users


bull Requirements

depend on use

of operation


Flight Operation)


Entitiesldquo

Pa

rt I-4

ndash L

ega

l Asp

ects



81

Pa

rt I-4

ndash L

ega

l Asp

ects



RPAS segments

82








rt I-4

ndash L

ega

l Asp

ects



RPAS segments









years



83

Pa

rt I-4

ndash L

ega

l Asp

ects






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Algorithm






(DLT)



60

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


ca

me

ras

points

61


Algorithm







calibration


new 3D points



triangulation


bundle adjustment

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


ca

me

ras

points

62


Algorithm







calibration


new 3D points



triangulation


bundle adjustment

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Algorithm


rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


Image Matching













64

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts











65






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


EduServ 12 (2014)


66





Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts

wwweurosdrnet



Legal Aspects



Geoinformatik


wwweurosdrnet









69









for subsequent use



rt I-4

ndash L

ega

l Asp

ects




70





rt I-4

ndash L

ega

l Asp

ects





Privacy


apply




72

Pa

rt I-4

ndash L

ega

l Asp

ects







growing


aviation background


before end 2020


73

Pa

rt I-4

ndash L

ega

l Asp

ects



Germany








(Permit required)




74

Pa

rt I-4

ndash L

ega

l Asp

ects


75



77



European Regulation

78





framework






Pa

rt I-4

ndash L

ega

l Asp

ects




79

Pa

rt I-4

ndash L

ega

l Asp

ects



3 Categories

80

Open Category


model planes

and UAS

ndash Geofencing

ndash Subcategories

in relation to

potential harm

ndash Exemption for

toys

ndash Control thru

police

Certified Category


UAS gt 25 kg

bull Certification

similar to

manned aviation

bull Pilot licence

(PPL)


Flight Operation

through Certified

Entities

Specific Category

bull Mostly for

commercial

UAS-users


bull Requirements

depend on use

of operation


Flight Operation)


Entitiesldquo

Pa

rt I-4

ndash L

ega

l Asp

ects



81

Pa

rt I-4

ndash L

ega

l Asp

ects



RPAS segments

82








rt I-4

ndash L

ega

l Asp

ects



RPAS segments









years



83

Pa

rt I-4

ndash L

ega

l Asp

ects



Algorithm






(DLT)



60

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


ca

me

ras

points

61


Algorithm







calibration


new 3D points



triangulation


bundle adjustment

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


ca

me

ras

points

62


Algorithm







calibration


new 3D points



triangulation


bundle adjustment

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Algorithm


rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


Image Matching













64

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts











65






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


EduServ 12 (2014)


66





Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts

wwweurosdrnet



Legal Aspects



Geoinformatik


wwweurosdrnet









69









for subsequent use



rt I-4

ndash L

ega

l Asp

ects




70





rt I-4

ndash L

ega

l Asp

ects





Privacy


apply




72

Pa

rt I-4

ndash L

ega

l Asp

ects







growing


aviation background


before end 2020


73

Pa

rt I-4

ndash L

ega

l Asp

ects



Germany








(Permit required)




74

Pa

rt I-4

ndash L

ega

l Asp

ects


75



77



European Regulation

78





framework






Pa

rt I-4

ndash L

ega

l Asp

ects




79

Pa

rt I-4

ndash L

ega

l Asp

ects



3 Categories

80

Open Category


model planes

and UAS

ndash Geofencing

ndash Subcategories

in relation to

potential harm

ndash Exemption for

toys

ndash Control thru

police

Certified Category


UAS gt 25 kg

bull Certification

similar to

manned aviation

bull Pilot licence

(PPL)


Flight Operation

through Certified

Entities

Specific Category

bull Mostly for

commercial

UAS-users


bull Requirements

depend on use

of operation


Flight Operation)


Entitiesldquo

Pa

rt I-4

ndash L

ega

l Asp

ects



81

Pa

rt I-4

ndash L

ega

l Asp

ects



RPAS segments

82








rt I-4

ndash L

ega

l Asp

ects



RPAS segments









years



83

Pa

rt I-4

ndash L

ega

l Asp

ects


ca

me

ras

points

61


Algorithm







calibration


new 3D points



triangulation


bundle adjustment

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


ca

me

ras

points

62


Algorithm







calibration


new 3D points



triangulation


bundle adjustment

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Algorithm


rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


Image Matching













64

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts











65






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


EduServ 12 (2014)


66





Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts

wwweurosdrnet



Legal Aspects



Geoinformatik


wwweurosdrnet









69









for subsequent use



rt I-4

ndash L

ega

l Asp

ects




70





rt I-4

ndash L

ega

l Asp

ects





Privacy


apply




72

Pa

rt I-4

ndash L

ega

l Asp

ects







growing


aviation background


before end 2020


73

Pa

rt I-4

ndash L

ega

l Asp

ects



Germany








(Permit required)




74

Pa

rt I-4

ndash L

ega

l Asp

ects


75



77



European Regulation

78





framework






Pa

rt I-4

ndash L

ega

l Asp

ects




79

Pa

rt I-4

ndash L

ega

l Asp

ects



3 Categories

80

Open Category


model planes

and UAS

ndash Geofencing

ndash Subcategories

in relation to

potential harm

ndash Exemption for

toys

ndash Control thru

police

Certified Category


UAS gt 25 kg

bull Certification

similar to

manned aviation

bull Pilot licence

(PPL)


Flight Operation

through Certified

Entities

Specific Category

bull Mostly for

commercial

UAS-users


bull Requirements

depend on use

of operation


Flight Operation)


Entitiesldquo

Pa

rt I-4

ndash L

ega

l Asp

ects



81

Pa

rt I-4

ndash L

ega

l Asp

ects



RPAS segments

82








rt I-4

ndash L

ega

l Asp

ects



RPAS segments









years



83

Pa

rt I-4

ndash L

ega

l Asp

ects


ca

me

ras

points

62


Algorithm







calibration


new 3D points



triangulation


bundle adjustment

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts



Algorithm


rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


Image Matching













64

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts











65






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


EduServ 12 (2014)


66





Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts

wwweurosdrnet



Legal Aspects



Geoinformatik


wwweurosdrnet









69









for subsequent use



rt I-4

ndash L

ega

l Asp

ects




70





rt I-4

ndash L

ega

l Asp

ects





Privacy


apply




72

Pa

rt I-4

ndash L

ega

l Asp

ects







growing


aviation background


before end 2020


73

Pa

rt I-4

ndash L

ega

l Asp

ects



Germany








(Permit required)




74

Pa

rt I-4

ndash L

ega

l Asp

ects


75



77



European Regulation

78





framework






Pa

rt I-4

ndash L

ega

l Asp

ects




79

Pa

rt I-4

ndash L

ega

l Asp

ects



3 Categories

80

Open Category


model planes

and UAS

ndash Geofencing

ndash Subcategories

in relation to

potential harm

ndash Exemption for

toys

ndash Control thru

police

Certified Category


UAS gt 25 kg

bull Certification

similar to

manned aviation

bull Pilot licence

(PPL)


Flight Operation

through Certified

Entities

Specific Category

bull Mostly for

commercial

UAS-users


bull Requirements

depend on use

of operation


Flight Operation)


Entitiesldquo

Pa

rt I-4

ndash L

ega

l Asp

ects



81

Pa

rt I-4

ndash L

ega

l Asp

ects



RPAS segments

82








rt I-4

ndash L

ega

l Asp

ects



RPAS segments









years



83

Pa

rt I-4

ndash L

ega

l Asp

ects



Algorithm


rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


Image Matching













64

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts











65






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


EduServ 12 (2014)


66





Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts

wwweurosdrnet



Legal Aspects



Geoinformatik


wwweurosdrnet









69









for subsequent use



rt I-4

ndash L

ega

l Asp

ects




70





rt I-4

ndash L

ega

l Asp

ects





Privacy


apply




72

Pa

rt I-4

ndash L

ega

l Asp

ects







growing


aviation background


before end 2020


73

Pa

rt I-4

ndash L

ega

l Asp

ects



Germany








(Permit required)




74

Pa

rt I-4

ndash L

ega

l Asp

ects


75



77



European Regulation

78





framework






Pa

rt I-4

ndash L

ega

l Asp

ects




79

Pa

rt I-4

ndash L

ega

l Asp

ects



3 Categories

80

Open Category


model planes

and UAS

ndash Geofencing

ndash Subcategories

in relation to

potential harm

ndash Exemption for

toys

ndash Control thru

police

Certified Category


UAS gt 25 kg

bull Certification

similar to

manned aviation

bull Pilot licence

(PPL)


Flight Operation

through Certified

Entities

Specific Category

bull Mostly for

commercial

UAS-users


bull Requirements

depend on use

of operation


Flight Operation)


Entitiesldquo

Pa

rt I-4

ndash L

ega

l Asp

ects



81

Pa

rt I-4

ndash L

ega

l Asp

ects



RPAS segments

82








rt I-4

ndash L

ega

l Asp

ects



RPAS segments









years



83

Pa

rt I-4

ndash L

ega

l Asp

ects


Image Matching













64

Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts











65






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


EduServ 12 (2014)


66





Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts

wwweurosdrnet



Legal Aspects



Geoinformatik


wwweurosdrnet









69









for subsequent use



rt I-4

ndash L

ega

l Asp

ects




70





rt I-4

ndash L

ega

l Asp

ects





Privacy


apply




72

Pa

rt I-4

ndash L

ega

l Asp

ects







growing


aviation background


before end 2020


73

Pa

rt I-4

ndash L

ega

l Asp

ects



Germany








(Permit required)




74

Pa

rt I-4

ndash L

ega

l Asp

ects


75



77



European Regulation

78





framework






Pa

rt I-4

ndash L

ega

l Asp

ects




79

Pa

rt I-4

ndash L

ega

l Asp

ects



3 Categories

80

Open Category


model planes

and UAS

ndash Geofencing

ndash Subcategories

in relation to

potential harm

ndash Exemption for

toys

ndash Control thru

police

Certified Category


UAS gt 25 kg

bull Certification

similar to

manned aviation

bull Pilot licence

(PPL)


Flight Operation

through Certified

Entities

Specific Category

bull Mostly for

commercial

UAS-users


bull Requirements

depend on use

of operation


Flight Operation)


Entitiesldquo

Pa

rt I-4

ndash L

ega

l Asp

ects



81

Pa

rt I-4

ndash L

ega

l Asp

ects



RPAS segments

82








rt I-4

ndash L

ega

l Asp

ects



RPAS segments









years



83

Pa

rt I-4

ndash L

ega

l Asp

ects











65






Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts


EduServ 12 (2014)


66





Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts

wwweurosdrnet



Legal Aspects



Geoinformatik


wwweurosdrnet









69









for subsequent use



rt I-4

ndash L

ega

l Asp

ects




70





rt I-4

ndash L

ega

l Asp

ects





Privacy


apply




72

Pa

rt I-4

ndash L

ega

l Asp

ects







growing


aviation background


before end 2020


73

Pa

rt I-4

ndash L

ega

l Asp

ects



Germany








(Permit required)




74

Pa

rt I-4

ndash L

ega

l Asp

ects


75



77



European Regulation

78





framework






Pa

rt I-4

ndash L

ega

l Asp

ects




79

Pa

rt I-4

ndash L

ega

l Asp

ects



3 Categories

80

Open Category


model planes

and UAS

ndash Geofencing

ndash Subcategories

in relation to

potential harm

ndash Exemption for

toys

ndash Control thru

police

Certified Category


UAS gt 25 kg

bull Certification

similar to

manned aviation

bull Pilot licence

(PPL)


Flight Operation

through Certified

Entities

Specific Category

bull Mostly for

commercial

UAS-users


bull Requirements

depend on use

of operation


Flight Operation)


Entitiesldquo

Pa

rt I-4

ndash L

ega

l Asp

ects



81

Pa

rt I-4

ndash L

ega

l Asp

ects



RPAS segments

82








rt I-4

ndash L

ega

l Asp

ects



RPAS segments









years



83

Pa

rt I-4

ndash L

ega

l Asp

ects


EduServ 12 (2014)


66





Pa

rt I-3

ndash D

ata

Acqu

isitio

n amp

Pro

ce

ssin

g C

on

ce

pts

wwweurosdrnet



Legal Aspects



Geoinformatik


wwweurosdrnet









69









for subsequent use



rt I-4

ndash L

ega

l Asp

ects




70





rt I-4

ndash L

ega

l Asp

ects





Privacy


apply




72

Pa

rt I-4

ndash L

ega

l Asp

ects







growing


aviation background


before end 2020


73

Pa

rt I-4

ndash L

ega

l Asp

ects



Germany








(Permit required)




74

Pa

rt I-4

ndash L

ega

l Asp

ects


75



77



European Regulation

78





framework






Pa

rt I-4

ndash L

ega

l Asp

ects




79

Pa

rt I-4

ndash L

ega

l Asp

ects



3 Categories

80

Open Category


model planes

and UAS

ndash Geofencing

ndash Subcategories

in relation to

potential harm

ndash Exemption for

toys

ndash Control thru

police

Certified Category


UAS gt 25 kg

bull Certification

similar to

manned aviation

bull Pilot licence

(PPL)


Flight Operation

through Certified

Entities

Specific Category

bull Mostly for

commercial

UAS-users


bull Requirements

depend on use

of operation


Flight Operation)


Entitiesldquo

Pa

rt I-4

ndash L

ega

l Asp

ects



81

Pa

rt I-4

ndash L

ega

l Asp

ects



RPAS segments

82








rt I-4

ndash L

ega

l Asp

ects



RPAS segments









years



83

Pa

rt I-4

ndash L

ega

l Asp

ects

wwweurosdrnet



Legal Aspects



Geoinformatik


wwweurosdrnet









69









for subsequent use



rt I-4

ndash L

ega

l Asp

ects




70





rt I-4

ndash L

ega

l Asp

ects





Privacy


apply




72

Pa

rt I-4

ndash L

ega

l Asp

ects







growing


aviation background


before end 2020


73

Pa

rt I-4

ndash L

ega

l Asp

ects



Germany








(Permit required)




74

Pa

rt I-4

ndash L

ega

l Asp

ects


75



77



European Regulation

78





framework






Pa

rt I-4

ndash L

ega

l Asp

ects




79

Pa

rt I-4

ndash L

ega

l Asp

ects



3 Categories

80

Open Category


model planes

and UAS

ndash Geofencing

ndash Subcategories

in relation to

potential harm

ndash Exemption for

toys

ndash Control thru

police

Certified Category


UAS gt 25 kg

bull Certification

similar to

manned aviation

bull Pilot licence

(PPL)


Flight Operation

through Certified

Entities

Specific Category

bull Mostly for

commercial

UAS-users


bull Requirements

depend on use

of operation


Flight Operation)


Entitiesldquo

Pa

rt I-4

ndash L

ega

l Asp

ects



81

Pa

rt I-4

ndash L

ega

l Asp

ects



RPAS segments

82








rt I-4

ndash L

ega

l Asp

ects



RPAS segments









years



83

Pa

rt I-4

ndash L

ega

l Asp

ects

wwweurosdrnet









69









for subsequent use



rt I-4

ndash L

ega

l Asp

ects




70





rt I-4

ndash L

ega

l Asp

ects





Privacy


apply




72

Pa

rt I-4

ndash L

ega

l Asp

ects







growing


aviation background


before end 2020


73

Pa

rt I-4

ndash L

ega

l Asp

ects



Germany








(Permit required)




74

Pa

rt I-4

ndash L

ega

l Asp

ects


75



77



European Regulation

78





framework






Pa

rt I-4

ndash L

ega

l Asp

ects




79

Pa

rt I-4

ndash L

ega

l Asp

ects



3 Categories

80

Open Category


model planes

and UAS

ndash Geofencing

ndash Subcategories

in relation to

potential harm

ndash Exemption for

toys

ndash Control thru

police

Certified Category


UAS gt 25 kg

bull Certification

similar to

manned aviation

bull Pilot licence

(PPL)


Flight Operation

through Certified

Entities

Specific Category

bull Mostly for

commercial

UAS-users


bull Requirements

depend on use

of operation


Flight Operation)


Entitiesldquo

Pa

rt I-4

ndash L

ega

l Asp

ects



81

Pa

rt I-4

ndash L

ega

l Asp

ects



RPAS segments

82








rt I-4

ndash L

ega

l Asp

ects



RPAS segments









years



83

Pa

rt I-4

ndash L

ega

l Asp

ects



69









for subsequent use



rt I-4

ndash L

ega

l Asp

ects




70





rt I-4

ndash L

ega

l Asp

ects





Privacy


apply




72

Pa

rt I-4

ndash L

ega

l Asp

ects







growing


aviation background


before end 2020


73

Pa

rt I-4

ndash L

ega

l Asp

ects



Germany








(Permit required)




74

Pa

rt I-4

ndash L

ega

l Asp

ects


75



77



European Regulation

78





framework






Pa

rt I-4

ndash L

ega

l Asp

ects




79

Pa

rt I-4

ndash L

ega

l Asp

ects



3 Categories

80

Open Category


model planes

and UAS

ndash Geofencing

ndash Subcategories

in relation to

potential harm

ndash Exemption for

toys

ndash Control thru

police

Certified Category


UAS gt 25 kg

bull Certification

similar to

manned aviation

bull Pilot licence

(PPL)


Flight Operation

through Certified

Entities

Specific Category

bull Mostly for

commercial

UAS-users


bull Requirements

depend on use

of operation


Flight Operation)


Entitiesldquo

Pa

rt I-4

ndash L

ega

l Asp

ects



81

Pa

rt I-4

ndash L

ega

l Asp

ects



RPAS segments

82








rt I-4

ndash L

ega

l Asp

ects



RPAS segments









years



83

Pa

rt I-4

ndash L

ega

l Asp

ects




70





rt I-4

ndash L

ega

l Asp

ects





Privacy


apply




72

Pa

rt I-4

ndash L

ega

l Asp

ects







growing


aviation background


before end 2020


73

Pa

rt I-4

ndash L

ega

l Asp

ects



Germany








(Permit required)




74

Pa

rt I-4

ndash L

ega

l Asp

ects


75



77



European Regulation

78





framework






Pa

rt I-4

ndash L

ega

l Asp

ects




79

Pa

rt I-4

ndash L

ega

l Asp

ects



3 Categories

80

Open Category


model planes

and UAS

ndash Geofencing

ndash Subcategories

in relation to

potential harm

ndash Exemption for

toys

ndash Control thru

police

Certified Category


UAS gt 25 kg

bull Certification

similar to

manned aviation

bull Pilot licence

(PPL)


Flight Operation

through Certified

Entities

Specific Category

bull Mostly for

commercial

UAS-users


bull Requirements

depend on use

of operation


Flight Operation)


Entitiesldquo

Pa

rt I-4

ndash L

ega

l Asp

ects



81

Pa

rt I-4

ndash L

ega

l Asp

ects



RPAS segments

82








rt I-4

ndash L

ega

l Asp

ects



RPAS segments









years



83

Pa

rt I-4

ndash L

ega

l Asp

ects





Privacy


apply




72

Pa

rt I-4

ndash L

ega

l Asp

ects







growing


aviation background


before end 2020


73

Pa

rt I-4

ndash L

ega

l Asp

ects



Germany








(Permit required)




74

Pa

rt I-4

ndash L

ega

l Asp

ects


75



77



European Regulation

78





framework






Pa

rt I-4

ndash L

ega

l Asp

ects




79

Pa

rt I-4

ndash L

ega

l Asp

ects



3 Categories

80

Open Category


model planes

and UAS

ndash Geofencing

ndash Subcategories

in relation to

potential harm

ndash Exemption for

toys

ndash Control thru

police

Certified Category


UAS gt 25 kg

bull Certification

similar to

manned aviation

bull Pilot licence

(PPL)


Flight Operation

through Certified

Entities

Specific Category

bull Mostly for

commercial

UAS-users


bull Requirements

depend on use

of operation


Flight Operation)


Entitiesldquo

Pa

rt I-4

ndash L

ega

l Asp

ects



81

Pa

rt I-4

ndash L

ega

l Asp

ects



RPAS segments

82








rt I-4

ndash L

ega

l Asp

ects



RPAS segments









years



83

Pa

rt I-4

ndash L

ega

l Asp

ects







growing


aviation background


before end 2020


73

Pa

rt I-4

ndash L

ega

l Asp

ects



Germany








(Permit required)




74

Pa

rt I-4

ndash L

ega

l Asp

ects


75



77



European Regulation

78





framework






Pa

rt I-4

ndash L

ega

l Asp

ects




79

Pa

rt I-4

ndash L

ega

l Asp

ects



3 Categories

80

Open Category


model planes

and UAS

ndash Geofencing

ndash Subcategories

in relation to

potential harm

ndash Exemption for

toys

ndash Control thru

police

Certified Category


UAS gt 25 kg

bull Certification

similar to

manned aviation

bull Pilot licence

(PPL)


Flight Operation

through Certified

Entities

Specific Category

bull Mostly for

commercial

UAS-users


bull Requirements

depend on use

of operation


Flight Operation)


Entitiesldquo

Pa

rt I-4

ndash L

ega

l Asp

ects



81

Pa

rt I-4

ndash L

ega

l Asp

ects



RPAS segments

82








rt I-4

ndash L

ega

l Asp

ects



RPAS segments









years



83

Pa

rt I-4

ndash L

ega

l Asp

ects



Germany








(Permit required)




74

Pa

rt I-4

ndash L

ega

l Asp

ects


75



77



European Regulation

78





framework






Pa

rt I-4

ndash L

ega

l Asp

ects




79

Pa

rt I-4

ndash L

ega

l Asp

ects



3 Categories

80

Open Category


model planes

and UAS

ndash Geofencing

ndash Subcategories

in relation to

potential harm

ndash Exemption for

toys

ndash Control thru

police

Certified Category


UAS gt 25 kg

bull Certification

similar to

manned aviation

bull Pilot licence

(PPL)


Flight Operation

through Certified

Entities

Specific Category

bull Mostly for

commercial

UAS-users


bull Requirements

depend on use

of operation


Flight Operation)


Entitiesldquo

Pa

rt I-4

ndash L

ega

l Asp

ects



81

Pa

rt I-4

ndash L

ega

l Asp

ects



RPAS segments

82








rt I-4

ndash L

ega

l Asp

ects



RPAS segments









years



83

Pa

rt I-4

ndash L

ega

l Asp

ects


75



77



European Regulation

78





framework






Pa

rt I-4

ndash L

ega

l Asp

ects




79

Pa

rt I-4

ndash L

ega

l Asp

ects



3 Categories

80

Open Category


model planes

and UAS

ndash Geofencing

ndash Subcategories

in relation to

potential harm

ndash Exemption for

toys

ndash Control thru

police

Certified Category


UAS gt 25 kg

bull Certification

similar to

manned aviation

bull Pilot licence

(PPL)


Flight Operation

through Certified

Entities

Specific Category

bull Mostly for

commercial

UAS-users


bull Requirements

depend on use

of operation


Flight Operation)


Entitiesldquo

Pa

rt I-4

ndash L

ega

l Asp

ects



81

Pa

rt I-4

ndash L

ega

l Asp

ects



RPAS segments

82








rt I-4

ndash L

ega

l Asp

ects



RPAS segments









years



83

Pa

rt I-4

ndash L

ega

l Asp

ects



77



European Regulation

78





framework






Pa

rt I-4

ndash L

ega

l Asp

ects




79

Pa

rt I-4

ndash L

ega

l Asp

ects



3 Categories

80

Open Category


model planes

and UAS

ndash Geofencing

ndash Subcategories

in relation to

potential harm

ndash Exemption for

toys

ndash Control thru

police

Certified Category


UAS gt 25 kg

bull Certification

similar to

manned aviation

bull Pilot licence

(PPL)


Flight Operation

through Certified

Entities

Specific Category

bull Mostly for

commercial

UAS-users


bull Requirements

depend on use

of operation


Flight Operation)


Entitiesldquo

Pa

rt I-4

ndash L

ega

l Asp

ects



81

Pa

rt I-4

ndash L

ega

l Asp

ects



RPAS segments

82








rt I-4

ndash L

ega

l Asp

ects



RPAS segments









years



83

Pa

rt I-4

ndash L

ega

l Asp

ects


European Regulation

78





framework






Pa

rt I-4

ndash L

ega

l Asp

ects




79

Pa

rt I-4

ndash L

ega

l Asp

ects



3 Categories

80

Open Category


model planes

and UAS

ndash Geofencing

ndash Subcategories

in relation to

potential harm

ndash Exemption for

toys

ndash Control thru

police

Certified Category


UAS gt 25 kg

bull Certification

similar to

manned aviation

bull Pilot licence

(PPL)


Flight Operation

through Certified

Entities

Specific Category

bull Mostly for

commercial

UAS-users


bull Requirements

depend on use

of operation


Flight Operation)


Entitiesldquo

Pa

rt I-4

ndash L

ega

l Asp

ects



81

Pa

rt I-4

ndash L

ega

l Asp

ects



RPAS segments

82








rt I-4

ndash L

ega

l Asp

ects



RPAS segments









years



83

Pa

rt I-4

ndash L

ega

l Asp

ects




79

Pa

rt I-4

ndash L

ega

l Asp

ects



3 Categories

80

Open Category


model planes

and UAS

ndash Geofencing

ndash Subcategories

in relation to

potential harm

ndash Exemption for

toys

ndash Control thru

police

Certified Category


UAS gt 25 kg

bull Certification

similar to

manned aviation

bull Pilot licence

(PPL)


Flight Operation

through Certified

Entities

Specific Category

bull Mostly for

commercial

UAS-users


bull Requirements

depend on use

of operation


Flight Operation)


Entitiesldquo

Pa

rt I-4

ndash L

ega

l Asp

ects



81

Pa

rt I-4

ndash L

ega

l Asp

ects



RPAS segments

82








rt I-4

ndash L

ega

l Asp

ects



RPAS segments









years



83

Pa

rt I-4

ndash L

ega

l Asp

ects



3 Categories

80

Open Category


model planes

and UAS

ndash Geofencing

ndash Subcategories

in relation to

potential harm

ndash Exemption for

toys

ndash Control thru

police

Certified Category


UAS gt 25 kg

bull Certification

similar to

manned aviation

bull Pilot licence

(PPL)


Flight Operation

through Certified

Entities

Specific Category

bull Mostly for

commercial

UAS-users


bull Requirements

depend on use

of operation


Flight Operation)


Entitiesldquo

Pa

rt I-4

ndash L

ega

l Asp

ects



81

Pa

rt I-4

ndash L

ega

l Asp

ects



RPAS segments

82








rt I-4

ndash L

ega

l Asp

ects



RPAS segments









years



83

Pa

rt I-4

ndash L

ega

l Asp

ects



81

Pa

rt I-4

ndash L

ega

l Asp

ects



RPAS segments

82








rt I-4

ndash L

ega

l Asp

ects



RPAS segments









years



83

Pa

rt I-4

ndash L

ega

l Asp

ects



RPAS segments

82








rt I-4

ndash L

ega

l Asp

ects



RPAS segments









years



83

Pa

rt I-4

ndash L

ega

l Asp

ects



RPAS segments









years



83

Pa

rt I-4

ndash L

ega

l Asp

ects

rpas in land survey - eurosdr · rpas in land survey eduserv14 ... rpas project design and flight...

Documents