Verfügbarkeit: Epipolar geometry in stereo, motion and object recognition

Epipolar geometry in stereo, motion and object recognition: a unified approach

Gespeichert in:

Bibliographische Detailangaben
Beteiligte Personen:	Xu, Gang (VerfasserIn), Zhang, Zhengyou (VerfasserIn)
Format:	Buch
Sprache:	Deutsch
Veröffentlicht:	Dordrecht [u.a.] Kluwer 1996
Schriftenreihe:	Computational imaging and vision 6
Schlagwörter:	Géométrie - Informatique Reconnaissance des formes (informatique) Traitement d'images Vision par ordinateur géométrie épipolaire localisation mouvement reconnaissance objet stéréovision Computer vision Image processing > Digital techniques Three-dimensional imaging Dreidimensionales maschinelles Sehen
Links:	http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=007383588&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA
Umfang:	XIX, 313 S. graph. Darst.
ISBN:	0792341996

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Datensatz im Suchindex

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adam_text	EPIPOLAR GEOMETRY IN STEREO, MOTION AND OBJECT RECOGNITION A UNIFIED APPROACH BY GANGXU DEPARTMENT OF COMPUTER SCIENCE, RITSUMEIKAN UNIVERSITY, KUSATSU, JAPAN AND ZHENGYOU ZHANG INRIA SOPHIA-ANTIPOLIS, SOPHIA-ANTIPOLIS, FRANCE KLUWER ACADEMIC PUBLISHERS DORDRECHT / BOSTON / LONDON CONTENTS FORWARD BY OLIVIER FAUGERAS XIII FORWARD BY SABURO TSUJI XV PREFACE XVII 1 INTRODUCTION L 1.1 VISION RESEARCH 1 1.2 MULTIPLE VIEW PROBLEMS IN VISION 2 1.3 ORGANIZATION OF THIS BOOK 4 1.4 NOTATION 5 2 CAMERA MODELS AND EPIPOLAR GEOMETRY 7 2.1 MODELING CAMERAS 7 2.-1.1 PINHOLE CAMERA AND PERSPECTIVE PROJECTION 7 2.1.2 PERSPECTIVE PROJECTION MATRIX AND EXTRINSIC PARAMETERS 10 2.1.3 INTRINSIC PARAMETERS AND NORMALIZED CAMERA 12 2.1.4 THE GENERAL FORM OF PERSPECTIVE PROJECTION MATRIX 14 2.2 PERSPECTIVE APPROXIMATIONS 16 2.2.1 ORTHOGRAPHIC AND WEAK PERSPECTIVE PROJECTIONS 17 2.2.2 PARAPERSPECTIVE PROJECTION 20 2.2.3 AFFINE CAMERAS 24 2.3 EPIPOLAR GEOMETRY UNDER FULL PERSPECTIVE PROJECTION 26 2.3.1 CONCEPTS IN EPIPOLAR GEOMETRY 26 2.3.2 WORKING WITH NORMALIZED IMAGE COORDINATES 29 VN VIII EPIPOLAR GEOMETRY 2.3.3 WORKING WITH PIXEL IMAGE COORDINATES 33 2.3.4 WORKING WITH CAMERA PERSPECTIVE PROJECTION MATRICES 37 2.3.5 FUNDAMENTAL MATRIX AND EPIPOLAR TRANSFORMATION 39 2.4 A GENERAL FORM OF EPIPOLAR EQUATION FOR ANY PROJECTION MODEL 42 2.4.1 INTERSECTING TWO OPTICAL RAYS 42 2.4.2 THE FULL PERSPECTIVE PROJECTION CASE 45 2.5 EPIPOLAR GEOMETRY UNDER ORTHOGRAPHIC, WEAK PERSPECTIVE, PARAPERSPECTIVE AND GENERAL AFHNE PROJECTIONS 46 2.5.1 ORTHOGRAPHIC AND WEAK PERSPECTIVE PROJECTIONS 47 2.5.2 PARAPERSPECTIVE PROJECTION 56 2.5.3 THE GENERAL AFFINE CAMERA 61 2.6 EPIPOLAR GEOMETRY BETWEEN TWO IMAGES WITH LENS DISTORTION 65 2.6.1 CAMERA DISTORTION MODELLING 66 2.6.2 COMPUTATING DISTORTED COORDINATES FROM IDEAL ONES 68 2.6.3 EPIPOLAR CONSTRAINT BETWEEN TWO IMAGES WITH DISTORTION 69 2.7 SUMMARY 70 2.A APPENDIX 71 2.A.I THIN AND THICK LENS CAMERA MODELS 71 2.A.2 INVERSE AND PSEUDOINVERSE MATRICES 75 RECOVERY OF EPIPOLAR GEOMETRY FROM POINTS 79 3.1 DETERMINING FUNDAMENTAL MATRIX UNDER FULL PERSPECTIVE PROJECTION 79 3.1.1 EXACT SOLUTION WITH 7 POINT MATCHES 81 3.1.2 ANALYTIC METHOD WITH 8 OR MORE POINT MATCHES 81 3.1.3 ANALYTIC METHOD WITH RANK-2 CONSTRAINT 87 3.1.4 NONLINEAR METHOD MINIMIZING DISTANCES OF POINTS TO EPIPOLAR LINES 88 3.1.5 NONLINEAR METHOD MINIMIZING DISTANCES BETWEEN OBSERVATION AND REPROJECTION 91 3.1.6 ROBUST METHODS 93 CONTENTS IX 3.1.7 CHARACTERIZING THE UNCERTAINTY OF FUNDAMENTAL MATRIX 106 3.1.8 AN EXAMPLE OF FUNDAMENTAL MATRIX ESTIMATION 111 3.1.9 DENNING EPIPOLAR BANDS BY USING THE ESTIMATED UNCERTAINTY 117 3.2 DETERMINING FUNDAMENTAL MATRIX FOR AFFINE CAMERAS 120 3.2.1 EXACT SOLUTION WITH 4 POINT MATCHES 121 3.2.2 ANALYTIC METHOD WITH MORE THAN 4 POINT MATCHES 121 3.2.3 MINIMIZING DISTANCES OF POINTS TO EPIPOLAR LINES 126 3.2.4 MINIMIZING DISTANCES BETWEEN OBSERVATION AND REPROJECTION 127 3.2.5 AN EXAMPLE OF AFFINE FUNDAMENTAL MATRIX ESTIMATION 129 3.2.6 CHARACTERING THE UNCERTAINTY OF AFFINE FUNDAMENTAL MATRIX 131 3.2.7 DETERMINING MOTION EQUATION IN THE 2D AFFINE MOTION CASE 133 3.3 RECOVERY OF MULTIPLE EPIPOLAR EQUATIONS BY CLUSTERING 136 3.3.1 THE PROBLEM IN STEREO, MOTION AND OBJECT RECOGNITION 137 3.3.2 DEFINITIONS AND ASSUMPTIONS 138 3.3.3 ERROR ANALYSIS OF MOTION PARAMETERS 139 3.3.4 ESTIMATING COVARIANCE MATRIX 141 3.3.5 THE MAXIMAL LIKELIHOOD APPROACH 142 3.3.6 ROBUST ESTIMATION USING EXPONENTIAL OF GAUSSIAN DISTRIBUTION 145 3.3.7 A CLUSTERING ALGORITHM 147 3.3.8 AN EXAMPLE OF CLUSTERING 148 3.4 PROJECTIVE RECONSTRUCTION 149 3.4.1 PROJECTIVE STRUCTURE FROM TWO UNCALIBRATED IMAGES 149 3.4.2 COMPUTING CAMERA PROJECTION MATRICES 151 3.4.3 RECONSTRUCTION TECHNIQUES 153 3.4.4 USE OF PROJECTIVE STRUCTURE 155 3.5 AFFINE RECONSTRUCTION 156 3.5.1 AFFINE STRUCTURE FROM TWO UNCALIBRATED AFFINE VIEWS 156 3.5.2 RELATION TO PREVIOUS WORK 159 3.5.3 EXPERIMENTAL RESULTS 159 EPIPOLAR GEOMETRY 3.6 SUMMARY 161 3.A APPENDIX 164 3.A.1 APPROXIMATE ESTIMATION OF FUNDAMENTAL MATRIX FROM GENERAL MATRIX 164 3.A.2 ESTIMATION OF AFFINE TRANSFORMATION 165 RECOVERY OF EPIPOLAR GEOMETRY FROM LINE SEGMENTS OR LINES 167 4.1 LINE SEGMENTS OR STRAIGHT LINES 168 4.2 SOLVING MOTION USING LINE SEGMENTS BETWEEN TWO VIEWS 173 4.2.1 OVERLAP OF TWO CORRESPONDING LINE SEGMENTS 173 4.2.2 ESTIMATING MOTION BY MAXIMIZING OVERLAP 175 4.2.3 IMPLEMENTATION DETAILS 176 4.2.4 RECONSTRUCTING 3D LINE SEGMENTS 179 4.2.5 EXPERIMENTAL RESULTS 180 4.2.6 DISCUSSIONS 192 4.3 DETERMINING EPIPOLAR GEOMETRY OF THREE VIEWS 194 4.3.1 TRIFOCAL CONSTRAINTS FOR POINT MATCHES 194 4.3.2 TRIFOCAL CONSTRAINTS FOR LINE CORRESPONDENCES 199 4.3.3 LINEAR ESTIMATION OF K, L, AND M USING POINTS AND LINES 200 4.3.4 DETERMINING CAMERA PROJECTION MATRICES 201 4.3.5 IMAGE TRANSFER 203 4.4 SUMMARY 204 REDEFINING STEREO, MOTION AND OBJECT RECOGNITION VIA EPIPOLAR GEOMETRY 205 5.1 CONVENTIONAL APPROACHES TO STEREO, MOTION AND OBJECT RECOGNITION 205 5.1.1 STEREO 205 5.1.2 MOTION 206 5.1.3 OBJECT RECOGNITION 207 5.2 CORRESPONDENCE IN STEREO, MOTION AND OBJECT RECOGNITION AS ID SEARCH 209 5.2.1 STEREO MATCHING 209 CONTENTS XI 5.2.2 MOTION CORRESPONDENCE AND SEGMENTATION 209 5.2.3 3D OBJECT RECOGNITION AND LOCALIZATION 210 5.3 DISPARITY AND SPATIAL DISPARITY SPACE 210 5.3.1 DISPARITY UNDER FULL PERSPECTIVE PROJECTION IN THE PARALLEL CAMERA CASE 211 5.3.2 DISPARITY UNDER FULL PERSPECTIVE PROJECTION IN THE GENERAL CASE 211 5.3.3 DISPARITY UNDER WEAK PERSPECTIVE AND PARAPERSPECTIVE PROJECTIONS 214 5.3.4 SPATIAL DISPARITY SPACE AND SMOOTHNESS 215 5.3.5 CORRESPONDENCE AS SEARCH FOR SURFACES AND CONTOURS IN SDS 218 5.4 SUMMARY 219 6 IMAGE MATCHING AND UNCALIBRATED STEREO 221 6.1 FINDING MATCH CANDIDATES BY CORRELATION 223 6.1.1 EXTRACTING POINTS OF INTEREST 223 6.1.2 MATCHING THROUGH CORRELATION 224 6.1.3 ROTATING CORRELATION WINDOWS 225 6.2 UNIQUE CORRESPONDENCE BY RELAXATION AND ROBUST ESTIMA- TION OF EPIPOLAR GEOMETRY FOR PERSPECTIVE IMAGES 227 6.2.1 MEASURE OF THE SUPPORT FOR A MATCH CANDIDATE 228 6.2.2 RELAXATION PROCESS 230 6.2.3 DETECTION OF FALSE MATCHES 232 6.3 UNIQUE CORRESPONDENCE BY ROBUST ESTIMATION OF EPIPOLAR GEOMETRY FOR AFFINE IMAGES 233 6.3.1 DISCARDING UNLIKELY MATCH CANDIDATES 233 6.3.2 GENERATING LOCAL GROUPS OF POINT MATCHES FOR CLUSTERING 234 6.4 IMAGE MATCHING WITH THE RECOVERED EPIPOLAR GEOMETRY 235 6.4.1 A SIMPLE IMPLEMENTATION FOR MATCHING CORNERS 236 6.4.2 A SIMPLE IMPLEMENTATION FOR MATCHING EDGES 236 6.5 AN EXAMPLE OF MATCHING UNCALIBRATED PERSPECTIVE IMAGES 237 6.6 AN EXAMPLE OF MATCHING UNCALIBRATED AFFINE IMAGES 241 6.7 SUMMARY 243 XII EPIPOLAR GEOMETRY 7 MULTIPLE RIGID MOTIONS: CORRESPONDENCE AND SEGMENTATION 247 7.1 PROBLEMS OF MULTIPLE RIGID MOTIONS 247 7.2 DETERMINING EPIPOLAR EQUATIONS FOR MULTIPLE RIGID MOTIONS 249 7.2.1 THE ALGORITHM 249 7.2.2 EXPERIMENTAL RESULTS 250 7.3 MATCHING AND SEGMENTING EDGE IMAGES WITH KNOWN EPIPOLAR EQUATIONS 253 7.3.1 REPRESENTING THE PROBLEM IN ESDS 253 7.3.2 A SUPPORT MEASURE FOR SELECTION FROM MULTIPLE CANDIDATES 255 7.3.3 EXPERIMENTAL RESULTS 256 7.4 TRANSPARENT MULTIPLE RIGID MOTIONS 258 7.5 SUMMARY AND DISCUSSIONS 260 7.6 APPENDIX: SVD ALGORITHM FOR STRUCTURE AND MOTION RE- COVERY WITH KNOWN EPIPOLAR EQUATIONS 263 8 3D OBJECT RECOGNITION AND LOCALIZATION 269 8.1 INTRODUCTION: 3D MODEL VS 2D MODEL, AND SINGLE MODEL VIEW VS. MULTIPLE MODEL VIEWS 269 8.2 RECOGNITION AND LOCALIZATION WITH SINGLE MODEL VIEW WITH MODEL VIEWS 271 8.2.1 IS A SINGLE VIEW SUFFICIENT FOR 3D OBJECT RECOGNITION? 271 8.2.2 MATCHING MODEL VIEW WITH INPUT VIEW AS UNCALIBRATED STEREO IMAGES 272 8.2.3 AN EXAMPLE 273 8.3 RECOGNITION AND LOCALIZATION WITH MULTIPLE MODEL VIEWS 278 8.3.1 INTERSECTION OF EPIPOLAR LINES 279 8.3.2 BASIS VECTORS 279 8.3.3 DETERMINING COEFFICIENTS 282 8.3.4 AN EXAMPLE 286 8.4 SUMMARY 287 9 CONCLUDING REMARKS 291 REFERENCES 293 INDEX 309
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id	DE-604.BV011027695
illustrated	Illustrated
indexdate	2024-12-20T10:05:04Z
institution	BVB
isbn	0792341996
language	German
oai_aleph_id	oai:aleph.bib-bvb.de:BVB01-007383588
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owner	DE-91G DE-BY-TUM DE-29T DE-83 DE-11
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physical	XIX, 313 S. graph. Darst.
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publisher	Kluwer
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series	Computational imaging and vision
series2	Computational imaging and vision
spellingShingle	Xu, Gang Zhang, Zhengyou Epipolar geometry in stereo, motion and object recognition a unified approach Computational imaging and vision Géométrie - Informatique ram Reconnaissance des formes (informatique) ram Traitement d'images ram Vision par ordinateur ram géométrie épipolaire inriac localisation inriac mouvement inriac reconnaissance objet inriac stéréovision inriac Computer vision Image processing Digital techniques Three-dimensional imaging Dreidimensionales maschinelles Sehen (DE-588)4137757-6 gnd
subject_GND	(DE-588)4137757-6
title	Epipolar geometry in stereo, motion and object recognition a unified approach
title_auth	Epipolar geometry in stereo, motion and object recognition a unified approach
title_exact_search	Epipolar geometry in stereo, motion and object recognition a unified approach
title_full	Epipolar geometry in stereo, motion and object recognition a unified approach by Gang Xu and Zhengyou Zhang
title_fullStr	Epipolar geometry in stereo, motion and object recognition a unified approach by Gang Xu and Zhengyou Zhang
title_full_unstemmed	Epipolar geometry in stereo, motion and object recognition a unified approach by Gang Xu and Zhengyou Zhang
title_short	Epipolar geometry in stereo, motion and object recognition
title_sort	epipolar geometry in stereo motion and object recognition a unified approach
title_sub	a unified approach
topic	Géométrie - Informatique ram Reconnaissance des formes (informatique) ram Traitement d'images ram Vision par ordinateur ram géométrie épipolaire inriac localisation inriac mouvement inriac reconnaissance objet inriac stéréovision inriac Computer vision Image processing Digital techniques Three-dimensional imaging Dreidimensionales maschinelles Sehen (DE-588)4137757-6 gnd
topic_facet	Géométrie - Informatique Reconnaissance des formes (informatique) Traitement d'images Vision par ordinateur géométrie épipolaire localisation mouvement reconnaissance objet stéréovision Computer vision Image processing Digital techniques Three-dimensional imaging Dreidimensionales maschinelles Sehen
url	http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=007383588&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA
volume_link	(DE-604)BV010119097
work_keys_str_mv	AT xugang epipolargeometryinstereomotionandobjectrecognitionaunifiedapproach AT zhangzhengyou epipolargeometryinstereomotionandobjectrecognitionaunifiedapproach

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