Motion and structure from image sequences:
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| Main Authors: | , , |
|---|---|
| Format: | Book |
| Language: | English |
| Published: |
Berlin u.a.
Springer
1993
|
| Series: | Springer series in information sciences
29 |
| Subjects: | |
| Online Access: | Inhaltsverzeichnis |
| Item Description: | Literaturverz. S. 423 - 439 |
| Physical Description: | XV, 444 S. Ill., graph. Darst. |
| ISBN: | 3540556729 0387556729 |
Staff View
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| 100 | 1 | |a Weng, Juyang |e Verfasser |4 aut | |
| 245 | 1 | 0 | |a Motion and structure from image sequences |c Juyang Weng ; Thomas S. Huang ; Narendra Ahuja |
| 264 | 1 | |a Berlin u.a. |b Springer |c 1993 | |
| 300 | |a XV, 444 S. |b Ill., graph. Darst. | ||
| 336 | |b txt |2 rdacontent | ||
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| 490 | 1 | |a Springer series in information sciences |v 29 | |
| 500 | |a Literaturverz. S. 423 - 439 | ||
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Record in the Search Index
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| adam_text | Contents
1. Introduction 1
1.1 Formulation of the Problem 2
1.2 Overview of Recent Progress 4
1.3 Bibliographical Notes 6
2. Image Matching 7
2.1 Approaches to Establishing Correspondences 7
2.2 An Approach to Image Matching 10
2.2.1 Image Attributes 12
2.2.2 Relationships of the Attributes 14
2.2.3 Intra Regional Smoothness and Occlusion 14
2.2.4 Multi Resolution Multi Grid Structure 17
2.2.5 Limitations 19
2.3 Algorithm 20
2.3.1 Locally Rigid Motion 20
2.3.2 3 D Motion and Image Plane Motion 21
2.3.3 Motion Insensitive Image Attributes 24
2.3.4 Edgeness and Cornerness 26
2.3.5 Smoothness 29
2.3.6 Minimizing Residuals 31
2.3.7 Recursive Blurring 34
2.3.8 Preprocessing and Normalization 35
2.3.9 Outline of the Matching Algorithm 37
2.4 Motion and Structure Computation 38
2.5 Refinements 39
X Contents
2.5.1 Bottom Up and Top Down 39
2.5.2 Refinement Based on Rigidity 40
2.6 Examples 41
2.7 Summary 59
2.8 Bibliographical Notes 61
Appendix 62
3. Two View Analysis 65
3.1 Some Basic Issues 65
3.2 An Algorithm 67
3.2.1 Problem Statement 68
3.2.2 Algorithm 70
3.2.3 Justification of the Algorithm 73
3.3 Error Estimation 78
3.3.1 Algorithm and Perturbation 79
3.3.2 Perturbation of Eigenvalues and Eigenvectors 81
3.3.3 Error Estimation for the Algorithm 83
3.4 Error Analysis 90
3.4.1 Structure of the Scene 90
3.4.2 Motion Parameters 91
3.4.3 System Parameters 97
3.5 Performance 98
3.5.1 Performance 99
3.5.2 Error Estimation 100
3.5.3 Error versus Motion and System Parameters 106
3.5.4 Real Images 115
3.6 Summary 117
3.7 Bibliographical Notes 118
Appendix 3.A Perturbation of Eigenspace 119
Appendix 3.B Quaternions 122
Appendix 3.C Alternative Fitting 125
4. Optimization 127
4.1 Motivations 127
4.2 Stability of Linear Algorithms 129
Contents XI
4.2.1 The Linear Algorithms 131
4.2.2 The Epipolar Constraint 132
4.2.3 Using the Constraint in Matrix E 134
4.2.4 A Type of Motion 135
4.2.5 Beyond the Epipolar Constraint 140
4.3 Maximum Likelihood Estimation 141
4.3.1 Gaussian Distribution 143
4.3.2 Uncertainty Polyhedron Distribution 146
4.4 A Two Step Approach and Computation 149
4.5 Minimum Variance Estimation 154
4.6 Error Estimation and Error Bounds 157
4.6.1 Error Estimation 157
4.6.2 Error Bounds 158
4.7 Batch and Sequential Methods 162
4.7.1 Linear Systems 163
4.7.2 Nonlinear Systems 166
4.7.3 Recursive Batch Solution 172
4.8 Numerical Examples 174
4.8.1 Whether a Good Initial Guess Is Necessary 174
4.8.2 Epipolar Improvement versus Optimization 175
4.8.3 Sequential versus Batch Solutions 176
4.8.4 Uncertainty Polyhedron Model 185
4.8.5 Error Estimation and Error Bound 188
4.8.6 Inherent Limitation of Optical Flow 193
4.8.7 Real World Images 195
4.9 Summary 195
4.10 Bibliographical Notes 197
Appendix 4.A Decomposability 197
Appendix 4.B Weights 199
Appendix 4.C Triangulation with Noise 200
Appendix 4.D Matrix Derivatives 202
Appendix 4.E Cram6r Rao Bound 203
5. Planar Scenes 205
5.1 Planar Scene as a Degenerate Case 205
XII Contents
5.2 Motion from a Plane 206
5.2.1 Problem Statement 206
5.2.2 Algorithm Overview 208
5.2.3 Intermediate Parameter Matrix F 209
5.2.4 General Case 211
5.2.5 Two Solutions Are Both Valid 216
5.2.6 Special Cases 218
5.3 Inherent Uniqueness 222
5.3.1 Decomposability 223
5.3.2 Rank Condition Is Algorithm Independent 225
5.3.3 The Fundamental Theorem 226
5.3.4 Plane Perceivable Surfaces 228
5.3.5 Optimality 230
5.3.6 Three View Problem 231
5.4 Examples 233
5.4.1 Simulations 233
5.4.2 Real Images 239
5.5 Conclusions 243
5.6 Bibliographical Notes 244
Appendix 5.A Conditions on the Rank of A 245
Appendix 5.B Two Solutions from F 248
Appendix 5.C Plane Perceivable Surfaces 249
Appendix 5.D Condition on Consistent Normals 250
Appendix 5.E Two View Algorithm 254
Appendix 5.F Error Estimation 257
6. From Line Correspondences 265
6.1 Lines as Features 265
6.2 Solution and Algorithm 266
6.2.1 Why Two Views Are Not Sufficient 267
6.2.2 From Three Views 268
6.2.3 Two Important Equations 269
6.2.4 A Geometrical View 270
6.2.5 Intermediate Parameters 272
6.2.6 Motion from Intermediate Parameters 274
Contents XDI
6.2.7 Structure and Sign of Translation Vectors 277
6.2.8 In the Presence of Noise 279
6.2.9 Algorithm 280
6.3 Degeneracy 284
6.4 Optimization 288
6.4.1 Lines from Pixels 288
6.4.2 Optimal Solution 290
6.4.3 How Accurate It Can Be 291
6.5 Simulations 292
6.5.1 Setup 292
6.5.2 Linear Algorithm 293
6.5.3 Algorithm with Optimization 297
6.5.4 Comparison with the Bound 301
6.5.5 Comparison with the Point Based Algorithm 301
6.6 Conclusions and Discussions 303
6.7 Bibliographical Notes 303
Appendix 6.A Ranks 304
Appendix 6.B Unique Consistent Assignment 308
Appendix 6.C Degeneracy 311
Appendix 6.D Distinct Locations Are Necessary 312
Appendix 6.E Alternative Degeneracy Condition 312
7. Stereo 315
7.1 Stereo Camera Systems 315
7.2 Stereo Triangulation 317
7.3 Closed Form Solution 320
7.3.1 A Matrix Weighted Objective Function 321
7.3.2 Unweighted and Scalar Weighted Versions 322
7.3.3 Matrix Weighted Least Squares Solution 322
7.3.4 Uniqueness 327
7.4 Iterative Optimal Solution 328
7.4.1 A Basic Objective Function 328
7.4.2 Optimization Using Space Decomposition 330
7.4.3 Estimating Errors 333
7.5 Outliers and Robust Estimators 335
XTV Contents
7.5.1 Some Basic Concepts of Robust Statistics 336
7.5.2 A Robust Method for Motion Estimation 337
7.5.3 Using Closed Form Solution 339
7.6 Examples 339
7.6.1 Simulations 340
7.6.2 Experiments with a Real Stereo Setup 348
7.7 Without Stereo Correspondences 355
7.7.1 Motivations 355
7.7.2 Motions Seen from Two Cameras 357
7.7.3 Determining Complete Motion and Structure 357
7.7.4 Computational Aspect of the Degeneracy 359
7.8 Long Image Sequences 361
7.8.1 Local and Global Coordinate Systems 363
7.8.2 A Recursive Batch Approach 364
7.8.3 Recursive Batch Updating 367
7.8.4 Local and Global Representations 368
7.8.5 Numerical Examples 371
7.9 Conclusions 376
7.10 Bibliographical Notes 377
Appendix 7.A MWCC Theorem 378
Appendix 7.B Least Squares Matrix Fitting 379
8. Motion Modeling and Prediction 381
8.1 Coherence of Motion 381
8.2 The LCAM Model 384
8.2.1 Motion of a Rigid Body in 3 D 384
8.2.2 Motion of Rotation Center 387
8.2.3 Solutions of the Coefficient Equation 391
8.2.4 Continuous and Discrete Motions 395
8.3 Estimation and Prediction 400
8.4 Monocular Vision 403
8.5 Optimization 406
8.6 Experimental Examples 408
8.6.1 Computer Simulation 408
8.6.2 Experiment with Real Images 412
Contents XV
8.7 Summary 413
8.8 Bibliographical Notes 414
Appendix 8.A Solution of Coefficient Equations 415
Appendix 8.B Rotation without Precession 420
Appendix 8.C Singularity of the Matrix 421
References 423
Subject Index 441
|
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| illustrated | Illustrated |
| indexdate | 2024-07-09T16:34:26Z |
| institution | BVB |
| isbn | 3540556729 0387556729 |
| language | English |
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| physical | XV, 444 S. Ill., graph. Darst. |
| publishDate | 1993 |
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| series | Springer series in information sciences |
| series2 | Springer series in information sciences |
| spelling | Weng, Juyang Verfasser aut Motion and structure from image sequences Juyang Weng ; Thomas S. Huang ; Narendra Ahuja Berlin u.a. Springer 1993 XV, 444 S. Ill., graph. Darst. txt rdacontent n rdamedia nc rdacarrier Springer series in information sciences 29 Literaturverz. S. 423 - 439 Computer vision Image processing Maschinelles Sehen (DE-588)4129594-8 gnd rswk-swf Bildfolgenverarbeitung (DE-588)4145414-5 gnd rswk-swf Maschinelles Sehen (DE-588)4129594-8 s Bildfolgenverarbeitung (DE-588)4145414-5 s DE-604 Huang, Thomas S. Verfasser aut Ahuja, Narendra Verfasser aut Springer series in information sciences 29 (DE-604)BV000008063 29 HBZ Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=003606270&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Weng, Juyang Huang, Thomas S. Ahuja, Narendra Motion and structure from image sequences Springer series in information sciences Computer vision Image processing Maschinelles Sehen (DE-588)4129594-8 gnd Bildfolgenverarbeitung (DE-588)4145414-5 gnd |
| subject_GND | (DE-588)4129594-8 (DE-588)4145414-5 |
| title | Motion and structure from image sequences |
| title_auth | Motion and structure from image sequences |
| title_exact_search | Motion and structure from image sequences |
| title_full | Motion and structure from image sequences Juyang Weng ; Thomas S. Huang ; Narendra Ahuja |
| title_fullStr | Motion and structure from image sequences Juyang Weng ; Thomas S. Huang ; Narendra Ahuja |
| title_full_unstemmed | Motion and structure from image sequences Juyang Weng ; Thomas S. Huang ; Narendra Ahuja |
| title_short | Motion and structure from image sequences |
| title_sort | motion and structure from image sequences |
| topic | Computer vision Image processing Maschinelles Sehen (DE-588)4129594-8 gnd Bildfolgenverarbeitung (DE-588)4145414-5 gnd |
| topic_facet | Computer vision Image processing Maschinelles Sehen Bildfolgenverarbeitung |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=003606270&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
| volume_link | (DE-604)BV000008063 |
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