nara women’s university automatic viewpoint selection for a visualization i/f in a pse machiko...

Nara Women’s University

Automatic Viewpoint Selection for a Visualization I/F in a PSE

Machiko Nakagawa, Masami Takata, Kazuki Joe



Outline

Background

Explain the Viewpoint Entropy

Proposal of View Potential

Experiment

Discussions

Conclusions & Future work


Background

？

？

ｙ -axis

x-axis

z-axis

data

etc.

time

Importance to select good viewpoints

Problem of viewpoint selectiona lot of visualized information

huge calculation cost of rendering

no criteria for good view

difficult to select good viewpointsNeed enough knowledge of data & visualization technique

Complex object

Large-scale data


View Selection in PSE

Possible visualization without expertise in PSE.

View selection by user

Eager of automatic viewpoint selectionpossibility of easier visualization

Technique of Automatic Viewpoint Selection with versatility


Definition of Good Views

No common definition

Local definitions depending on each purpose

Necessary information 　→　 visibility

Unnecessary information 　→　 invisibility

information

NEED USELESS

Good View


Previous Works

Vázquez, “Viewpoint Selection Using Viewpoint Entropy“(2001)

A viewpoint definition by information theoryShannon’s Entropy

Viewpoint Entropyprojected Area

the number of visible faces


Viewpoint Entropy

fN

i t

i

t

i

A

A

A

ApSI

0

log),(

Nf ： the number of faces of the scene

Ai ： projected area of a face i

A0 ： projected area of

the background in open scenes

At ： the total projected area of the scene


Re-experiment of Viewpoint Entropy (1/2)

projected area is moved.

The number of visible faces is constant

As the projected area increases, Viewpoint Entropy increases

best view

Movement of a camera

RE-1


Re-experiment of Viewpoint Entropy(2/2)

best view

As the number of visible faces increases, Viewpoint Entropy increases

The number of visible faces is increased.

The projected area is almost same as the previous experiment

RE-2


A Problem of Viewpoint Entropy

The same Viewpoint Entropy value

Difference in information of views


Improvement of Viewpoint Entropy

Only two properties for viewpoint selection

No other properties which should beBrightness, Color,etc.

plural properties to obtain better views

View Potential

problems of Viewpoint Entropy

Improvement of evaluation method


Proposal of View Potential

W0 ： projected area　&

the number of visible faces

W1 ： luminance

W2 ： chrominance

W3 ： weight of objects

3,3,2,2,1,1,0,0

0, **)***( iiiiiii

n

ii WAWAWAWAW


W1: Luminance(1/2)

Brightness is more sensitive than color difference for human perception

EX) Dark place and/or very small object

Dark picture

Bright picture

Luminance is important for scene recognition.

Recognize shape(brightness)

Unrecognize

color difference


W1: Luminance(2/2)

Calculation of viewpoint selection with view luminance

YIQ Color System 　【 Y(Luminance ） ,I & Q(Chrominance ）】

Y = 0.2990 * R + 0.5870 * G + 0.1140 * B

I = 0.5959 * R - 0.2750 * G + 0.3210 * B

Q = 0.2065 * R - 0.4969 * G - 0.2904 * B

convert RGB into YIQ


Luminance Property

What’s a good view in luminance ?

The value of luminance diffuses.

Larger dispersion in luminance should be selected.


Difficult

Easy

W2: chrominance

cognition is difference in hue

red-green

yellow-blue RGB Color System

L*a*b*Color System

different impressions by color mapping

chrominance in data

chrominance in perception

bury the difference of

color recognition!


Chrominance Property

Views with higher space frequency are more recognizable.

The use of a differentiation filter

edge


W3:Weight objects

Weight each object as the importance degree

The weight of unnecessary objects is 0Reduction of calculation cost

No Need

weight:0

weight:2

Need

weight:1


Visualization Pipeline (1/2)

vtkRender

vtkRenderWindow

vtk3DSImporter

BYU Data

3DS Data

vtkPolyDataMapper

vtkCubeSource

vtkActor

vtkPolyDataMapper

vtkPolyDataNomals

vtkActor

vtkBYUReader

Create Scene

* Generate a Scene *The polygon object is set up

in vtkRenderWindow


Pipeline of visualization(2/2)

vtkRenderWindow

vtkActorCollection

vtkActor

vtkTriangleFilter

vtkMassEntropy

GetInformation

NULL

ActorList

Calculate Entropy

take out an Actor of the scene.

calculate each object.

Implemented library

To use vtkMassEntropy

the cell of the polygon is

normalized. calculate information


Input the weight of each object

Input data necessary for calculation

Calculate contrast

Calculate chrominance

Calculate the Viewpoint Entropy

vtkMassEntropy

vtkMassEntropy

Functions

GetEntropy()

GetCont(vktRenderer)

GetChromi()

SetActors(vtk ActorCollection)

SetWeight(int)

SetInput(vtkPolyData);


Viewpoint Entropy+ Luminance

Add the property of brightness to RE-1

entropy entrpy ＋ luminance

Select asymmetry and a contrasty view

RE-3


Experiment of Chrominance ： Data description

・ Height： Latitude

・Width： Longitude

・ time： altitude

・ color： temperature

ECMWFThe European Center for Medium-range Weather Forecastsprovide temperature data of the atmosphere.（ 1991/1/1)

RE-4


Comparison of images from experiment results (1/2)

Large deviation Small deviation

High appraisal Low appraisal


Comparison of images from experiment result (2/2)

Almost same by human vision



Change hue

The impression changes by hue

Complex temperature change Simple temperature change



Weighting Objects:Environment

A scene with several objects

A camera moves

with a constant distance around the focus point.

RE-5


Weighting Objects

set a value to this object

weightingno weighting


ViewSet

Change the coefficients of each property

A set of good viewpoints


Discussions

luminancecalculating the contrast of the whole scene,

The detail of an object might not be presented.

improvement by the information of color difference

chrominanceNot only the chrominance values but also the chrominance degree based on human perception

application of texture mapping etc.


Conclusions

An automatic and general viewpoint selection technique is proposed.

View Potential with plural properties is defined.

Experiments with some scenes, and selection of good views


Future works

reduction of calculate costCPU GPU

use of general purpose shade pipes

calculate vtk library → 　 directX or OpenGL

decrease the number of calculating points.How to move camera

Appropriate coefficient for each property by GUI

nara women’s university automatic viewpoint selection for a visualization i/f in a pse machiko...

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