3dm analyst mine mapping suite training jason birch, managing director adam technology...

3DM Analyst Mine Mapping SuiteTraining

Jason Birch, Managing DirectorADAM Technology

[email protected] http://www.adamtech.com.au

Copyright © 2009 ADAM Technology

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Mining Analysis Software

3DM Analyst

• Principles of Photogrammetry

• Project Types

• Case Studies

• Camera Settings

• Orientations

• Convergent Models

Presentation Overview

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Principals of Photogrammetry

Photogrammetry is the science of using 2D images to make accurate measurements in 3D. To do that, the information that was lost when the image was captured needs to be recovered.

The location of any point in an image canbe described with just two co-ordinates:(x,y). Images are only two-dimensional.

The location of any point in the real worldcan be described by three co-ordinates:(x,y,z), (latitude, longitude, altitude), etc.The real world is three-dimensional.

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Problem: The light that hits a given pixel in the image could have come from any point along the ray from the pixel, through the perspective centre, into the scene.

Possible points of origin

Top-down view

ImageSensor

FocalLength

Perspective Centre

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Solution: Adding another image taken from a different location allows us to intersect the rays and determine the 3D location of the point where the light came from!

Top-down view

ImageSensor Unique 3D location!

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Exterior Orientation

Image Matching

Principals of PhotogrammetryInformation needed to determine 3D locations:

1. The location of each camera’s perspective centre.

2. The orientation (rotation) of each camera about its perspective centre.

3. The location of the point on each image sensor.

This is the essence of photogrammetry!

3DM Analyst Mine Mapping Suite determines thesecompletely automatically.

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Important Characteristics of Photogrammetry• Relatively range-invariant — simply choose the lens required to

obtain the desired ground pixel size:

sensorpixelsize

f

distanceground

pixelsize

Object

Image

FocalLength

Image

FocalLength

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Important Characteristics of Photogrammetry• Accuracy highly configurable — planimetric accuracy depends

on image accuracy and ground pixel size; depth accuracy additionally depends on camera separation:

(previous slide)

Good values for :

0.5: Conservative value for planning

0.3: Reasonable estimator of actual accuracy in most cases

0.05: Best value actually observed (circular targets)

planbase

distancedepth

groundpixelsize

pixelplan

pixel

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Visualising Accuracy• The relationship between accuracy in the image, planimetric

accuracy, depth accuracy, and base:distance ratio can be visualised by looking at the “error ellipse” that is formed when we adjust the location of the point in each image by the image accuracy:

Error Ellipse

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Visualising Accuracy• Increasing the base relative to the distance makes the error

ellipse more circular, improving the depth accuracy:

Error Ellipse

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3D Point Accuracy (1-sigma)

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Canon EOS 5D 50mm (1:3)





Canon EOS 1Ds Mark II 600mm (1:5)


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3D Point Accuracy (1-sigma)

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Optech ILRUS-3D-ER

Leica ScanStation

Riegl LMS-420i

I-Site 4400LR

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Limitations of Photogrammetry• Surface must be textured — image matching doesn’t work on

featureless surfaces

• Natural surfaces are usually sufficiently textured

• Pattern projector can be used

• Targets can be used

• Must be able to see every point of interest from two locations — “shadowing” effect is twice as bad as a laser scanner

• Taking additional images from different vantage points to fill in the shadows doesn’t add much time

• Subject should look similar in each image

• Change in brightness or colour doesn’t matter; having lots of shadows in one (e.g. captured late afternoon) and no shadows in the other (e.g. captured mid-day) hinders matching because shadows look “interesting”

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Digital photogrammetric system designed to work with modern digital cameras:

• Automatically determines relationships between camera positions (relative orientation) simply by inspecting images

• Automatically generates 3D surface data fromimagery

• Powerful vector data digitising and editingtools with 4 billion user-definedfeature types allowed

• Extensive operator assistance whenever human input is required

• Built-in digital camera calibration routines

3DM Analyst Mine Mapping Suite

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3DM Analyst Mine Mapping Suite• 3DM CalibCam

• Performing camera calibrations (interior orientations)

• Determining exterior orientations (camera positions and directions) for any number of images simultaneously

• Surveying targets accurately (up to 80,000:1!)

• Creating extremely high-resolution merged images

• 3DM Analyst• Generating, editing, and merging DTMs

• Digitising vector data using Single Image mode, Stereo, or 3D mode

• Analysing data — volume calculations, face detection, etc.

• Exporting data as 3D Images, DXF, etc.

• DTM Generator• Generating DTMs and resulting 3D Images in batch mode

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Workflow

Capture Images

Determine camera orientations

Generate DTMs & 3D Images (if required)

3DM CalibCamor 3DM Analyst

3DM Analyst orDTM Generator

Analyse data: calculate volumes, digitise vector data, etc.3DM Analyst,

Vulcan,Surpac, etc.

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Fieldwork Planning

Techniques to ensure:

• That every point of interest is seen from two locations

• That the data can be georeferenced in the desired co-ordinate system

• Most common: survey at least three locations (control points and/or camera stations)

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Independent Models• Pair of images of the same area taken from two different locations

Pros:

• Conceptual simplicity

• Flexibility — depth accuracy can be freely adjusted by changing base, can be used with lenses of any focal length over any distance

Cons:

• Each model needs to be fully controlled (at least three known locations — control points and (optionally) camera stations)

• Vulnerable to bad control due to low level of redundancy if very few control points are used per model due to the total number required

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Image Fans• Series of images overlapping neighbours by about 10% captured from

each camera station, generally from far away with long focal length lens

Pros:

• Fewer unknowns give strong orientations with very few control points — minimum is one control point plus two camera stations or three control points for entire project, no matter how many images are used!

• Very fast — rotating camera to capture next area much quicker than relocating camera, allowing large areas to be captured efficiently

• Images can be merged (and treated as independent models in 3DM Analyst) allowing very high resolution images with cheap cameras

First model Second model

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Image Strips• Series of parallel images overlapping neighbours by 60%.

(May be arranged in multiple rows, overlapping about 25%.)

Pros:

• Gives accurate exterior orientations with very few control points — one control point for every five images is generally more than adequate

• Ideal for aerial imagery

Cons:

• Base is determined by field of view, which is determined by focal length — best with short focal lengths

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Case Studies

The difference between theory and practice is that, in theory, there isn’t any…

Yogi Berra

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Image Fans, Painted Control • Camera: Canon EOS 5D, 100 mm lens

• Project area: 390 m × 190 m

• Number of images: 12

• Number of camera stations: 2

• Distance to pit wall: 450 m

• Ground pixel size: ~4 cm

• Number of control points: six, three painted on top bench and three painted at base of wall

• Accuracy: Sx = 0.04 m, Sy = 0.02 m, Sz = 0.03 m.

• Capturing time: 25 minutes

• Processing time: 15 minutes (4 minutes user time)

• Points generated: 1.5 million

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Image Fans, Painted Control • Camera: Nikon 1Ds, 135mm lens


• Number of images: 27 from each station



• Ground pixel size: 3 cm

• Number of control points: 7 (around top of the pit)

• Accuracy: Sx = 0.14 m, Sy = 0.08 m, Sz = 0.04 m

• Capturing time: ~ 30 minutes (est.)

• Processing time: 1 hour 38 minutes (8 minutes user time)

• Points generated: 9.5 million

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Image Fans, Painted Control • Camera: Canon EOS 5D, 200 mm lens






• Number of control points: 50

• Accuracy: Sx = 0.09 m, Sy = 0.11 m, Sz = 0.08 m

• Capturing time: 30 minutes

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Image Strip (car), Painted Control • Camera: Canon 5D, 28 mm lens





• Number of control points: 3

• Capturing time: < 2 minutes

• Processing time: < 20 minutes

• Points generated: 2 million

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Image Fans, “Natural” Control • Camera: Canon EOS 5D, 50/100/200 mm lens


• Number of images: 4/13/48



• Ground pixel size: 10/5/2.5 cm

• Number of control points: one (delineator on top of wall) plus two surveyed camera stations

• Capturing time: 15 minutes (<10 minutes without 200 mm images)

• Processing time: 6/13/33 minutes

• Points generated: 0.8/2/7 million

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Image Fans, “Natural” Control • Camera: Canon 5D,

50/100/200 mm lens


• Number of images: 7/17/70


• Distance to pit wall: 85 m (base)

• Ground pixel size: 14/7/3.5 mm

• Number of control points: 10 (natural points, reflectorless TS)

• Capturing time: 10 minutes (all three lenses)

• Processing time: 13/30/128 minutes

• Points generated: 0.7/4.5/16 million points

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No control! • Camera: Canon 5D, 28 mm lens




• Distance to pit wall: 85 m (base)

• Ground pixel size: 2.5 cm

• Number of control points: 0(three surveyed camera stations)

• Capturing time: 1 minute 54 seconds

• Processing time: 2 minutes 15 seconds

• Points generated: 255,000

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Aerial Images (Strips), Marked Control (UAV)• 330 m x 260 m stockpile pad

(8.6 hectares, 21 acres)

• 7 minutes of flying(30 minutes in the field)

• 30 minutes processing

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Aerial Images (Strips), Marked Control (UAV)• Over 15 million points

(175 points/m2)

• 20 mm accuracy

• Clear view of entire stockpile surface

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Aerial Images (Strips), Marked Control (UAV)

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UAV

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Camera Settings

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Camera Settings

Zoom

• Largest single effect on calibration accuracy — ensure zoom is consistent with that used for calibration! (Generally means only minimum and maximum zoom can be used.)

• Prime lenses are generally cheaper and sharper than zoom lenses (simpler construction), and cannot accidentally use the wrong zoom.

Focus

• Second largest effect on the accuracy of a camera calibration — ensure focal distance is consistent with that used for calibration!

• For outdoor work, generally focus at infinity and rely on depth of field to keep scene in focus. (Use the autofocus to focus on an object distance (cloud, mountain, etc.) to ensure focus is at infinity — manually setting focus to limit can actually focus “beyond” infinity!)

• Generally recommend using Auto Focus but beware of focus changing between images on the same camera station — can use auto focus for the first image then switch off for the others on the same station.

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Camera Settings (cont.)Aperture

• Small effect on calibration accuracy. Try to ensure aperture remains consistent or have a range of calibrations for different aperture settings.

• Specified in terms of diameter of aperture in relation to focal length, f. f/8 means diameter of aperture is 1/8th of the focal length.

• Smaller apertures increase depth of field. Too small and light refraction blurs image.

• Recommended range: f/5.6 – f/11.0. Optimal: f/8.0.

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Camera Settings (cont.)ISO Speed Setting

• Unlike film, image sensor actually has a constant speed. Higher speeds simulated by applying a gain, amplifying noise => bad for image matching. Use the lowest speed setting supported by your camera, recommended set to ISO 100.

Shutter speed

• Aperture, ISO Speed Setting, and Shutter Speed control image exposure. Aperture affects calibration, ISO Speed Setting affects noise => only Shutter Speed can be used to obtain the correct exposure.

• On a bright sunny day, using an aperture of f/8 and ISO 100, correct exposure time is around 1/200th to 1/250th second — fast enough to hand-hold the camera. On overcast days, when shutter speed must be slower than 1/200th of a second, make sure to use a tripod. Also consider remote shutter release (to reduce movement when pressing the button) and mirror lockup option on SLRs (to reduce vibration).

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Taking Images

Lighting

• Changes in lighting between images causes problems with image matching. The software can compensate for a great deal of difference in brightness between images, but changing the light source location changes the shape of shadows, which can cause difficulties matching. Do not use the camera’s built-in flash!

Movement

• If an object moves between images it may be correctly identified and matched in each image, but because it moved the location will be wrong.

Regular features

• Can cause spikes in images if incorrectly matched, especially horizontal features such as fence rails or scaffolding.

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Orientations

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Terminology: Interior/Exterior• Interior Orientation/Camera Calibration — the parameters inside the

camera: focal length, principal point offset, radial lens distortions, etc. All images in a given project will usually have the same interior orientation.

• Exterior Orientation — the parameters outside the camera: position (x,y,z) and orientation (omega, phi, kappa). Each image in a project will have a unique exterior orientation.

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Camera CalibrationIn the earlier diagrams we assumed that light travels straight through the lens to the image sensor. This is not the case! The actual image can deviate considerably from the ideal one.

In addition to determining the precise focal length, 3DM Analyst and 3DM CalibCam correct for the following deviations from an ideal lens:

1. Principal point offset: Xp and Yp. (Compensates for the optical centre of the lens not aligning with the centre of the image sensor.)

2. Radial lens distortions: K1, K2, K3, and K4.

3. Decentring distortion: P1 and P2. (Compensates for misalignment of lens elements with each other.)

4. Scaling factors: B1 and B2. (Compensates for differential scaling in X and Y and non-perpendicularity of the image axes.)

Typical deviation after calibration: 0.1 to 0.2 pixels!

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Camera Calibration (cont.)• In 3DM Analyst, the additional unknowns to be solved means the

minimum number of known 3D locations increases from three (to find exterior orientations) to at least eight (to perform camera calibration) — preferably many more! Recommended minimum: 18 points.

• 3DM CalibCam can perform a calibration without control point at all by using additional images, but adding additional images allows accuracy estimates to be made. Recommended minimum: 6 images.

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Camera Calibration (cont.)• Control configuration is very important. Ensure a good spread of

points in all three dimensions: never allow all known 3D locations to be colinear (straight line) and do not all them all to be coplanar if you are doing a camera calibration! The Calibration Report generated by 3DM CalibCam should be checked before accepting calibration.

• Ensure there are control points (or relative-only points that appear in three images if possible) that extend all the way to the edge of the image.

• Rotate the camera 90 degrees to capture additional images in portrait mode to strengthen the calibration.

• Calibration files can be freely shared between 3DM Analyst and 3DM CalibCam.

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Camera Calibration (cont.)

2/3

1/3

Object distance

Station 1

Station 2 Station 3

Station 4 Station 5 Station 6

Ideal Image geometry for a calilbration project:

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Terminology: Relative/AbsoluteInterior or Exterior Orientations have two sub-categories:

• Relative Orientation (Free Network) — one that is formed without using control points or camera stations, usually based on an arbitrary local co-ordinate system, and usually used when data does not need to be registered in real-world co-ordinates. Known distances between camera locations or points in the image (e.g. scale bars) can be used to obtain correct scaling.

• Absolute Orientation (Control Network)— one that uses control points and/or camera stations to register data in a real-world co-ordinate system.

Both methods can actually be used for registering data in a real-world co-ordinate system if desired, but it is easier to do so with an absolute orientation. Relative orientations should be used when the real-world co-ordinates do not matter and you only need the correct scale.

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Determining OrientationsGiven image co-ordinates of a point (x, y) in two images, and knowing the cameras’ exterior orientations, we can determine the 3D ground co-ordinates of that point.

Can also work backwards: Given the image co-ordinates of several points in two images, and knowing the 3D ground co-ordinates of those points, we can also determine camera’s exterior orientations!

At least three known locations (control points and/or camera stations) are required for a single project. For 3DM Analyst, this means three per two images. For 3DM CalibCam, can be any number of images. More is always better, however.

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How does it work?The software uses an algorithm called a Least Squares Bundle Block Adjustment.

“Least Squares”: the solution found is the one that minimises the square of the error of each observation in terms of their individual sigmas.

“Bundle”: the rays connecting each point in 3D with the associated point on the image sensor, passing through each camera’s perspective centre, resembles a bundle.

“Block”: A single row of images is called a strip of images. A project with multiple rows of images is called a block. 3DM Analyst only solves for one model (two images) at a time, so “Block” is omitted.

Usually abbreviated to “Bundle Adjustment”.

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ResectionThe Bundle Adjustment algorithm can find the optimal solution in a least-squares sense, but only if it is given an initial solution that is already approximately correct.

A Resection is used to find that initial approximation.

3DM Analyst implicitly performs a resection before each Bundle Adjustment.

3DM CalibCam separates the two. A resection should be performed first, followed by a bundle adjustment. Once a solution has been found, you can re-do the bundle adjustment (e.g. after adding or deleting points) without doing the resection again.

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Determining Exterior Orientations(or Bundle Adjustment)

Inputs:• Image co-ordinates of all control points, and Auto Relative only points

• Image co-ordinate sigmas (Sx,Sy)

• Control point co-ordinates if any

• Camera station co-ordinates if any

• Individual co-ordinate sigmas for both control points and camera stations (Sx,Sy,Sz) if any

Outputs:• Adjusted image co-ordinates for all points (RO points)

• Adjusted control point co-ordinates if any

• Exterior orientations

• Derived ground co-ordinates for all of the RO points.

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Summary• Photogrammetry determines 3D locations by intersecting rays from

the corresponding pixel in each image through the perspective centre of each image.

• Perspective centre locations and orientations (exterior orientations) are determined by the software by looking at the locations in each image of corresponding points and working backwards.

• Camera calibrations (interior orientations) are determined in exactly the same way, but require more images or control points because more parameters need to be solved.

• The easiest way to register data in real-world co-ordinates is to use control points and/or surveyed camera stations and perform an absolute orientation.

• At least three known locations in a triangle shape are required to register the data for a project. More locations add redundancy and robustness.

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Convergent Models

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Independent Models• Pair of images of the same area taken from two different locations

Pros:

• Conceptual simplicity

• Flexibility — depth accuracy can be freely adjusted by changing base, can be used with lenses of any focal length over any distance

Cons:

• Each model needs to be fully controlled (at least three known locations — control points and (optionally) camera stations)

• Vulnerable to bad control due to low level of redundancy if very few control points are used per model due to the total number required

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Step 1: Project Setup (3DM Analyst)

Using the New Project Wizard:

1. Project type: Digital Camera Project.

2. Specify left and right images. (Software will detect later on if the images are in the wrong order and offer to swap them.)

3. Specify the camera calibration file.

4. Specify the control point file. (Simple ASCII text file containing both control points and surveyed camera positions, if used. Note: co-ordinates must be X,Y,Z / East, North, Height, i.e. right-handed co-ordinate system. Surveyors often give data as North, East, Height, so first two columns must be swapped. 3DM CalibCam has a button to do this for you.)

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1. Digitise control points:

• Circular targets: use target centroiding tool ( ); just click near the target and the software will find the centre very accurately(< 0.1 pixels)

• Other types: use natural point digitising tool ( ). When you have digitised it in one image, the software will use that to refine the point you digitise in the other image.

2. Press . The software will search for additional common points in the images (relative-only points — points for which 3D locations are unknown) and then perform a bundle adjustment to determine camera orientations. If successful, the bundle adjustment report will indicate the quality of the orientations.

Step 2: Orientations

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Step 2: Orientations

3. If everything is fine, press OK and the software will proceed to generate the Digital Terrain Model (DTM/3D Image).

Should be similarto survey accuracy Should be similar

to calibrationaccuracy (0.1-0.2)

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1. Click on the 3D View tab at the bottom of the window to switch to the main view that is used for mapping.

2. Initial view will be a wireframe. Click on the Show Triangles button ( ) to deactivate it and drape the image over the surface model.

3. To manipulate the view:

• Left mouse button + mouse movement = rotation

• Right mouse button + mouse movement = translation

• Both mouse buttons + vertical mouse movement = zoom

• Both mouse buttons + horizontal mouse movement = rotation

4. Note that view manipulation using the mouse is (almost) always active; to actually digitise points we use a “3D cursor” rather than the mouse directly.

Step 3: Mapping

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Step 3: Mapping — Feature Definitions

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• The 3D cursor is used for digitising data. To make it follow the mouse (on the DTM) hold down the Ctrl key or turn it on and off by pressing the Tab key; at any time, while digitising a feature, the view can be changed without affecting the feature being digitised.

• Press the Centre On Cursor button ( ) to centre the view on the 3D cursor — useful for checking the flatness of a feature while digitising it.

Step 3: Mapping — 3D Cursor

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1. Press ‘f’ to start digitising a new feature.

2. Press the spacebar to add a point (the current location of the 3D cursor) to the feature.

3. Press ‘s’ to save the feature.

Step 3: Mapping — Digitising Features

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• The number of points added to a plane feature determines how it is generated:

• 1 point — the software will attempt to “grow” a plane from the digitised points using the parameters in the Discontinuity Analysis dialog and find the least squares bet fit plane for the points it determines belong to the same face. Only useful for planes. (Automatic face detection uses the same technique but will detect all flat surfaces larger than the user-specified size.)

• 2 points — allow you to directly specify the origin and the normal of the plane.

• 3+ points — the software will find the least squares bet fit plane to the points you have digitised. Useful for both faces and traces.

Step 3: Mapping — Digitising Features

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1. Move the 3D cursor near a feature and press the Enter key to snap on to it.

2. Press ‘i’ to bring up the Feature Info dialog box.

3. Click on “Measure” and snap on to the next feature in the set to measure the spacing (and relative angle).

4. Export using Feature Info |Feature info List. CSV formatis best.

Step 3: Mapping — Feature Info

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Image Fans

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Image Fans• Series of images overlapping neighbours by about 10% captured from

each camera station, generally from far away with long focal length lens

Pros:

• Fewer unknowns give strong orientations with very few control points — minimum is one control point plus two camera stations or three control points for entire project, no matter how many images are used!

• Very fast — rotating camera to capture next area much quicker than relocating camera, allowing large areas to be captured efficiently

• Images can be merged (and treated as independent models in 3DM Analyst) allowing very high resolution images with cheap cameras

First model Second model

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Step -1: DTM Generator

1. Double-click on the DTM Generator icon to launch DTM Generator.

2. Click on the close box in the top-right corner of the window to exit.

(This step only needs to be completed once after the software has been installed, just so 3DM CalibCam knows where

DTM Generator is. In the future this step will not be necessary.)

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Step 0: Camera Setup (3DM CalibCam)

1. Right-click on Camera DataBase, select Add New Camera.

2. Click Read...

3. Open the .cal file for the camera to be used.

(This step is usually not required because the camera will already be in your database.)

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Step 1: Project Setup (3DM CalibCam)

1. Left-click on the camera in the Camera DataBase and drag it onto New Project.

2. Right-click on the camera, select Add Image.

3. Select all of the images in the project and click Open.

4. Right-click DataSet, select Add Data Set. Click on Browse to specify the control point file, then specify the units and click OK. (Simple ASCII text file containing both control points and surveyed camera positions, if used. Note: co-ordinates must be X,Y,Z / East, North, Height, i.e. right-handed co-ordinate system. Surveyors often give data as North, East, Height, so first two columns must be swapped. To do this, double-click on the control point file under Data Set and click Swap XY.)

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Step 1: Project Setup (Cont.)

5. Right-click on the camera and select Add Camera Station.

6. Under Station without Control Point, click Add once for each camera station.

7. Select the images taken from each station and drag them onto the appropriate station.

(These steps are only necessary if you have taken more than one image from each location, or if you have surveyed camera locations. In the latter case, use Station with Control Point and choose the point ID that is acting as a camera station from the list and click Add.)

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The relative orientations are the orientations (position and direction) of the cameras in an arbitrary co-ordinate system.

1. Select Digitising Tools | Generate Relative-Only Points and press Start. (This can take a very long time for large projects with hundreds of images.)

Relative-only points are common points between images for which 3D co-ordinates are not provided to the software. The software uses these to determine the relative orientations. Because their precise locations are unimportant, the software can generate these automatically. If it is having difficulty finding common points, or if there are particular locations in the images that you wish to determine 3D data for, you can digitise additional relative-only points by hand.

Step 2: Relative Orientations

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2. Press Close. Select Exterior | Free Network and click on Resection. The software will attempt to determine the approximate orientations of the cameras. (Resection is very clever but not all that accurate — it’s job is to start with no knowledge about the camera orientations and come up with an approximate solution that’s good enough for the next step.)

Step 2: Relative Orientations (Cont.)

Can be quite large at this stage;

problems occur when the values are

100s of pixels or more

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3. If the resection is successful, click OK, then Adjust — the software will now attempt to refine that initial approximation and produce an accurate solution. If successful, click Close.


Should be similar to calibrationaccuracy (0.1-0.3).

If larger it indicates thepresence of bad RO points,

bad calibration, or somethingwrong with the images

(images on wrong station,images changing focus

between images on samestation, etc.)

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4. Choose Edit | Remove Bad Relative-Only Points and click OK to have the software search for possible bad points and remove them.

5. Reselect Exterior | Free Network, Adjust to redo the bundle adjustment with any bad points removed. (It is not necessary to redo the resection because the solution from last adjustment should be fine as an approximate solution this time.)

At this point, if the RMS Pt (Pixel) values are not within the calibration accuracy, it is worth investigating (starting with the images with the largest values). If you see lots of points with tails, and the tails are in a pattern (adjacent points have similar sized tails in a similar direction) then it indicates a systematic problem (calibration, wrong camera station, changing focus, not rotating about the perspective centre). If random, suspect more bad points — repeat the last two steps.


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1. Digitise control points:

• Circular targets: use target centroiding tool ( ); just click near the target and the software will find the centre very accurately(< 0.1 pixels)

• Other types: use natural point digitising tool ( ):

Step 3: Absolute Orientations

Use sliders to adjust zoom and appearance to

make it easier to digitise accurately

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Natural point digitising operation:

i. Make sure the control point ID in the toolbar is correct:

ii. Move the mouse to the approximate location and press ‘l’ to lock the view.

iii. Use the arrow keys to refine the position. (Press Shift to move faster.) Make sure the mouse is over the background window or the arrow keys will move the last slider you touched instead!

iv. Press Spacebar to digitise the point.

v. Repeat for a total of three control points in two images each. The two images for each control point must be captured from two different locations. (You can have all three points in each of two images, or one point per image, or any combination thereof.)

Step 3: Absolute Orientations (Cont.)

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2. Press Close. Select Exterior | Control Network and click on Resection. The software will attempt to determine the approximate orientations of the cameras, this time in the desired real-world co-ordinate system.


Values should be similar to last free network

resection.

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3. If the resection is successful, click OK, then Adjust — the software will now attempt to refine that initial approximation and produce an accurate solution. If successful, click Close.


Should be similar to calibration accuracy

(0.1-0.3).

Not yet reliable, only three points in use. Will tend to

be very small.

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4. Digitise remaining control points:

• Circular targets: visit each image and use driveback tool ( ).

• Other types: use natural point digitising tool again, but this time ask it to drive to the approximate location of each point. Hold down:

Shift — to skip over already-digitised points

Ctrl — to only consider control points

and click on Next to go to the next undigitised control point. Digitise it as before and repeat until all control points digitised — the software will visit every undigitised control point in every image in turn.

If the positions that the dialog drives to are still quite far from the correct locations, after digitising a few additional points try doing Exterior | Control Network | Adjust again, then continue.


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4. Perform a final absolute adjustment (Exterior | Control Network | Adjust) and verify the accuracy results are within the expected range. Save the project.


Should now be within expected values given survey accuracy and

expected project accuracy.

If not, view the Control Points RMS Error Summary table in the HTML Report

for highlighted control points to investigate.

The Trouble Shooting button on the Exterior Orientation — Control Network dialog will also

check the control points for you and inform you if any

are suspect.

Check to view detailed HTML

report.

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Step 4: Image Merging

1. Right-click on a camera station and select Create Merged Images. (Choosing the left camera station will ensure all DTMs generated later are colour-balanced.)

2. Adjust the area to be included in the merged image to be created by dragging on the blue boxes in the image preview.

3. Specify the file name (e.g. Station1.jpg, Left.jpg, ...) and click Add/Update.

4. Click Create and Close when finished.

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Step 5: DTM Generation (Option 1)

(This option allows you to combine a single merged image with multiple original images from the other station. It has the advantage that each DTM/project remains small and easy to manage, while still removing the need for each image to line up with the corresponding image in the other station.)

• After making sure the project is saved, right-click on the same camera station and select Remove Camera Station.

• Right-click on the project and select Add Image. Select the merged image just created. If the software warns you that the point IDs overlap and asks if you want to shift them, select No.

• Select Report | Image Pair List.

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4. Select Report | Image Pair List.

5. In the Image Pairs Report, click on the checkbox on each row then click Generate Names.

6. Make sure Launch DTM Generator is selected then click Create Projects. (Make sure you have run DTM Generator at least once prior to this, even if you just close it again afterwards. See Step -1.)

7. Click on Check All to verify all projects are in order, then Generate DTMs.

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(This option allows you to create two merged images and process them as a convergent model. It has the advantage that you only have a single DTM, but be making the merged images too large can cause memory problems.)

• Repeat Step 4 for the other camera station, creating an appropriately-named image (Station2.jpg, Right.jpg, …)

• Launch 3DM Analyst as per the Convergent Models case, but do not specify a camera calibration in Step 1 point 3 (specifying a control point file in Step 1 point 4 is optional) and do not digitise any control points in Step 2 (they will already be digitised). When you press “GO”, 3DM Analyst will recognise that the orientations have already been performed and will skip straight to the DTM generation phase.

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Step 6: Mapping, Etc.

Each project created by DTM Generator can now be loaded directly into 3DM Analyst for mapping.

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Image Strips

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Image Strips• Series of parallel images overlapping neighbours by 60%.

(May be arranged in multiple rows, overlapping about 25%.)

Pros:

• Gives accurate exterior orientations with very few control points — one control point for every five images is generally more than adequate

• Ideal for aerial imagery

Cons:

• Base is determined by field of view, which is determined by focal length — best with short focal lengths

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Image Strips (3DM CalibCam)

Exactly the same as image fans, except:

• Skip points 5-7 in Step 1 because there are no camera stations.

• Skip Step 4 because there is no image merging.

(Note that you can use a strip of merged images if you wish — same as image fans, but there are more than two camera stations.)

3. Follow only steps 3-7 of Step 5 (Option 1) to use DTM Generator to generate the DTMs in batch mode. Alternatively, after saving the project in 3DM CalibCam, you can run the New Project Wizard in 3DM Analyst as per the Convergent Models case, but do not specify a camera calibration in Step 1 point 3. (Specifying a control point file in Step 1 point 4 is optional.)

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