Perceptual Organization for Artificial Vision Systems

350 Pages·2000·18.269 MB·English

by  Kim L. Boyer, Sudeep Sarkar (auth.), Kim L. Boyer, Sudeep Sarkar (eds.)

PERCEPTUAL ORGANIZATION FOR
ARTIFICIAL VISION SYSTEMS
THE KLUWER INTERNATIONAL SERIES
IN ENGINEERING AND COMPUTER SCIENCE
PERCEPTUAL ORGANIZATION FOR
ARTIFICIAL VISION SYSTEMS
Edited by
KIML. BOYER
The Ohio State University, Columbus
SUDEEPSARKAR
University of South Florida, Tampa
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"
Springer Science+Business Media, LLC
Library of Congress Cataloging-in-Publication
Perceptual organization for artificial vision systems 1 edited by Kim L. Boyer, Sudeep Sarkar.
p. cm. --(Kluwer international series in engineering and computer science ; SECS 546)
Includes bibliographicaI references and index.
ISBN 978-1-4613-6986-8 ISBN 978-1-4615-4413-5 (eBook)
DOI 10.1007/978-1-4615-4413-5
I. Computer vision. 2. VisuaI perception. 3. üptical pattern recognition. I. Boyer, Kim
L. 11. Sarkar, Sudeep. III. Series.
TA1634 .P47 2000
006.3'7--dc21
00-022754
Copyright 2000 by Springer Science+Business Media New York
@
Originally published by Kluwer Academic Publishers, New York in 2000
Softcover reprint of the hardcover 1s t edition 2000
All rights reserved. No part of this publication may be reproduced, stored in a retrievaI system or
transmitted in any form or by any means, mechanicaI, photo-copying, recording, or otherwise, without
the prior written permission of the publisher, Springer Science+Business Media, LLC.
Printed on acid-ji-ee paper.
Contents
ContributingAuthors xi
1
Introduction
Kim L. Boyer, SudeepSarkar
1. Introduction 1
2. TheBreakoutReports 4
3. ASnapshot: IssuesfromtheFloor 7
4. Research Contributions: Perceptual Psychology meets Computer
Vision 9
5. ConclusionsandRecommendations 11
PartI FocusedDeliberations
2
PrinciplesandMethods 17
DavidJacobs, JitendraMalik, RamNevatia
1. Introduction 17
2. Goalsofperceptualorganization 18
3. Stateofthe art 20
4. Futuredirections 22
3
LearningandPerceptualOrganization 29
EricSaund, JonasAugust, JoachimBuhmann, DanielCrevier,
GreetFrederix, DannyRoobaert
1. Introduction 29
2. Whatis thereto learninPO? 30
3. CommonPerceptualOrganizationEngine 30
4. TrainingData 31
5. Why islearningimportant? 32
4
SpatiotemporalGrouping 33
Kim L. Boyer, DanielFagerstrom, MichaelKubovy, PeterJohansen,
SudeepSarkar
1. Introduction 33
2. ThreeBasicParadigms 34
3. TheQuestions 36
4. ConclusionsandRecommendations 37
vi PERCEPTUALORGANIZATION
PartII Discoursesin Human and MachineVision
5
Gestalt: FromPhenomenatoLaws 41
Michael Kubovy, SergeiGepshtein
1. Introduction 41
2. GroupingbyProximityinSpace 43
3. GroupingbyProximityandSimilarity 49
4. GroupingbyProximityin Space-Time 54
6
ConvexityinPerceptualCompletion 73
vv.
ZiliLiu, David Jacobs, RonenBasri
1. Introduction 73
2. Computationaltheories 74
3. Psychologicaltheories 75
4. Theconvexitytheory 75
5. Groupinganddepthdiscrimination 77
6. Experiment1: 79
7. Experiment2 83
8. Discussion 87
7
AGestaltModelofSpatialPerception 91
StevenLehar
1. Introduction 92
2. TheGestaltPropertiesofPerception 94
3. TheComputationalMechanismofPerception 99
4. AGestaltBubbleModel 101
5. BrainAnchoring 115
6. Conclusion 116
8
WhatMakes ViewpointInvariantPropertiesPerceptuallySalient? 121
DavidJacobs
1. Introduction 121
2. ViewpointInvarianceinComputationalGrouping 122
3. ViewpointInvarianceinPoints 123
4. OtherGestaltproperties 131
5. Discussion: WhyMinimalFeatures? 132
9
ContourandTextureAnalysisforImageSegmentation 139
JitendraMalik, SergeBelongie, ThomasLeung, Jianbo Shi
1. Introduction 139
2. Filters,CompositeEdgels,andTextons 145
3. TheNormalizedCutFramework 153
4. DefiningtheWeights 154
5. ComputingtheSegmentation 161
6. Results 165
Contents vii
10
PerceptualOrganizationforGenericObjectDescription 173
R. Nevatia
1. Introduction 173
2. TheRoleofPerceptualOrganization 174
3. SaliencyofFeatures 176
4. An ApproachtoPerceptualOrganization 177
5. SomeSystemRealizations 179
6. CombiningEvidence,UncertaintyReasoningandMachineLearning 185
7. Conclusions 187
11
TowardRicherLabelsforVisualStructure 191
EricSaund
1. Introduction 191
2. TheStrengthofWeakModels 192
3. PerceptualOrganizationinDocumentImages 194
4. PerceptualOrganizationinPosterizedScenes 201
5. Conclusion 210
12
TensorVoting 215
Chi-KeungTang, Mi-SuenLee, GerardMedioni
1. Introduction 215
2. Previouswork 216
3. Salientinferenceengineoverview 218
4. Tensorrepresentation 219
5. Tensorcommunication 222
6. Featureextraction 225
7. Complexity 227
8. Results in2-D 227
9. Results in3-D 230
10. Conclusion 234
11. Softwaresystems 235
13
Anobservationonsaliency 239
MichaelLindenbaum,AlexanderBerengolts
1. Introduction 239
2. ProbabilisticSaliency 241
3. Theprobabilisticsaliencyoptimizationprocess 242
4. Implementation 245
5. Conclusion 246
14
ClosedCurvesin theAnalysisandSegmentationofImages 249
K. K. Thornber, L. R. Williams
1. Motivation 249
2. Theory 250
3. Results 258
4. Conclusion 262
viii PERCEPTUALORGANIZATION
15
Thecurveindicatorrandomfield: Curveorganizationviaedgecorrelation 265
JonasAugust. Steven W Zucker
1. Introduction 265
2. OverviewofOurProbabilisticModelforCurveOrganization 268
3. TheUnderlyingCurveFieldModel 268
4. TheOrientedWienerFilter 272
5. ValidatingtheEdgeCorrelationAssumption 276
6. Summary 286
16
EulerSpiralforShapeCompletion 289
BenjaminB. Kimia, /lana Frankel, Ana-MariaPopescu
1. Introduction 290
2. Euler'sSpiral 296
3. Euler'sSpiralforBoundaryModelingand GapCompletion 299
4. BiarcConstructionandInterpolation 300
5. Examples 304
6. SummaryandDiscussion 305
17
BayesianExtractionofCollinearSegmentChainsfrom DigitalImaJ5e.\ 311
DanielCrevier
1. Introduction 311
2. EdgeDetectionand Linking 313
3. DeviationMeasures 313
4. UnderlyingAccidentalDistributions 314
5. PriorAccidentalDensitiesofDeviationMeasures 315
6. ExtractionofthePriorProbabilityofNon-accidentalJunctions 316
7. ExtractionofNon AccidentalJunctions 317
8. ExtractionofCandidateChains 317
9. ValidationofChains 318
10. IterativeProcedure 319
11. ExamplesandConclusion 319
18
ObjectDetectionbyMultiprimitivePreattentivePerceptualOrganization 325
Pascal Vasseur, ElMustaphaMouaddib, Claude Pegard, ArnaudDupuis
1. Introduction 326
2. PreviousWork 328
3. TheMulti-primitivePre-attentiveApproach 330
4. ExperimentalResults 339
5. Conclusion 343
Index 347
This bookisdedicatedtothe
mysteryofperception
Contributing Authors
Jonas August,Yale University
[email protected]
Ronen Basri, TheWeizmannInstituteofScience, Israel
[email protected]
AlexanderBerengolts, Technion, Israel
SergeBelongie, University ofCalifornia, Berkeley
[email protected]
KimL. Boyer, DepartmentofElectricalEngineering
TheOhio StateUniversity, Columbus, Ohio
[email protected]
Joachim Buhmann, UniversitatBonn
Daniel Crevier, OphthalmosSystems Inc., Montreal,
[email protected]
Arnaud Dupuis, G.R.A.C.S.Y., France
IlanaFrankel, BrownUniversity
GreetFrederix, Katholieke UniversiteitLeuven
[email protected]
Sergei Gepshtein, University ofVirginia,
[email protected]
DavidJacobs, NEC Research Institute,
[email protected]
BenjaminB. Kimia, BrownUniversity,
[email protected]