Representation and recognition in vision:
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
Cambridge, Mass. [u.a.]
MIT Press
1999
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| Schriftenreihe: | A Bradford book
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| Schlagworte: | |
| Online-Zugang: | Inhaltsverzeichnis |
| Beschreibung: | 335 S. Ill., graph. Darst. |
| ISBN: | 0262050579 |
Internformat
MARC
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Datensatz im Suchindex
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|---|---|
| adam_text | Acknowledgments xiii
Introduction xv
1 The Problem of Representation 1
1.1 A Vision of Representation 1
1.2 Reconstruction 4
1.3 Representation without Reconstruction 6
1.3.1 The Feature Detector Redux 7
1.3.2 The Challenge 9
2 Theories of Representation and Object Recognition 11
2.1 Recognition Related Tasks That Require Representation 11
2.1.1 Identification and Generalization 13
2.1.2 Categorization 15
2.1.3 Analogy 17
2.2 A Formalization of the Notion of Representation 19
2.2.1 The Problem of Representation 19
2.2.2 Representation as a Mapping 20
2.2.3 First and Second Order Isomorphism 21
2.3 Computational Theories of Recognition 27
2.3.1 Reconstructionist Theories: A Brief Historical
Perspective 27
2.3.2 Structural Decomposition Theories 29
2.3.3 Theories Based on Geometric Constraints 33
2.3.4 Multidimensional Feature Spaces 35
viii Contents
3 S isomorphism: The Theory 43
3.1 Similarity as Proximity in a Metric Space 45
3.1.1 Some Common Objections 45
3.1.2 A Metric Similarity Space as a Working Hypothesis 49
3.2 Shape Spaces 49
3.2.1 Kendall s Shape Space 49
3.2.2 Transformations and Deformations 50
3.2.3 Best Correspondence Distance 52
3.2.4 An Objective Shape Space 53
3.3 Parameterization of Distal Shape Space 53
3.3.1 Scope of Parameterization 55
3.3.2 Dimensionality of Parameterization 58
3.4 The Distal to Proximal Mapping 62
3.4.1 Levels of Representation of Similarity 63
3.4.2 The Components of the Mapping F 64
3.4.3 Constraints on F 66
3.4.4 Implications 68
4 S isomorphism: An Implementation 75
4.1 Task Dependent Treatment of the Measurement Space 78
4.1.1 Identification ( Is this an image of object X? ) 78
4.1.2 Recognition ( Is this an image of something I
know? ) 86
4.1.3 Categorization ( What is this thing? ) 87
4.2 Categorization as Navigation in Shape Space 94
4.2.1 Defining the Frame of Reference 95
4.2.2 Active Landmarks 96
4.3 Tuned Units as Active Landmarks 98
4.3.1 Relevance 98
4.3.2 Coverage 98
4.3.3 Smoothness 98
4.3.4 Invariance to Irrelevant Dimensions 99
4.3.5 Monotonicity 101
4.3.6 Learnability 103
4.4 The Chorus of Prototypes 105
4.4.1 Persistent and Ephemeral Representations 106
Contents ix
4.4.2 The Underlying Principles 107
4.4.3 The Applications 108
5 S isomorphism: Experiments 111
5.1 A Chorus of Ten Reference Object Modules 113
5.1.1 The RBF Module 114
5.1.2 A Multiple Module Network 114
5.2 Experimental Results: Recognition Related Tasks 116
5.2.1 Identification of Novel Views of Familiar Objects 116
5.2.2 Categorization of Novel Object Views 118
5.2.3 Discrimination Among Views of Novel Objects 124
5.3 Experimental Results: Analogy Related Tasks 126
5.3.1 Mechanism for Supporting Analogy 128
5.3.2 Local Viewpoint Invariance for Novel Objects 131
5.3.3 Recovery of a Standard View for Novel Objects 131
5.3.4 Recovery of Pose for Novel Objects 133
5.3.5 Prediction of View for Novel Objects 133
5.3.6 Comparison with Related Methods 133
5.4 Interim Summary: Second Order Isomorphism and Chorus
(SiC) 140
6 Biological Evidence 145
6.1 Neurobiology: Computing with Receptive Fields 145
6.2 Neurobiology: Properties of RFs at the Lower Levels of
Processing 147
6.2.1 Broad Tuning 147
6.2.2 Graded Response 147
6.3 Neurobiology: Properties of RFs at the Higher Levels of
Processing 147
6.3.1 Selectivity to Objects 149
6.3.2 Ensemble Encoding 152
6.3.3 Selective Invariance 156
6.3.4 Plasticity and Learning 160
6.3.5 Speed of Processing 161
6.3.6 A Summary of Neurobiological Support for SiC 162
6.4 Psychophysics: Effects of Viewpoint 163
6.4.1 Canonical Views 163
x Contents
6.4.2 Mental Rotation 165
6.4.3 Nonlinearities and the Effects of Practice 169
6.4.4 A Model of Canonical Views and Mental Rotation 173
6.4.5 Viewpoint Invariance as a Tool for Testing Theories of
Representation 176
6.5 Psychophysics: Veridicality of Shape Representation 197
6.5.1 Perceived Similarity as Proximity in an Internal Metric
Space 199
6.5.2 Veridical Perception of Distal Shape Contrasts 200
6.6 Psychophysics: Effects of Translation 206
6.6.1 Translation Invariance for Line Drawings of Common
Objects 208
6.6.2 Translation Invariance for Controlled Synthetic
Animal like Shapes 209
7 Dialogues on Representation and Recognition 219
7.1 Dialogue 1: On the Problem of Representation 220
7.2 Dialogue 2: On Theories of Representation 227
7.3 Dialogue 3: On S isomorphism 229
7.4 Dialogue 4: On the Chorus of Prototypes 232
7.5 Dialogue 5: On the Performance of Chorus 234
7.6 Dialogue 6: On Representation and Recognition in Biological
Vision 237
7.7 Dialogue 7: On What Has Been Left Out of This Book 243
Appendix A The Measurement Space and the Distal to Proximal
Mapping 257
A.I The View Space 259
A.2 The Shape Space 259
Appendix B Representation by Distances to Prototypes 263
B.I The Chorus Transform 263
B.I.I Distance Rank Preservation by CT 263
B.I.2 Bounds on Dimensionality Reduction: The Embedding
Theorems 264
B.1.3 CT As an Implementation of Bourgain s Method 265
B.1.4 Non expansion of Distances by CT 267
B.1.5 Preservation of Voronoi Structure by CT 268
B.2 Representation by Rank Order of Distances to Prototypes 269
Contents xi
Appendix C Quasiconformal Mappings and Deformable Shapes 273
Appendix D RBF Modules for Object Representation 275
D.I Radial Basis Function (RBF) Approximation 275
D.2 Theoretical Aspects of RBF Module Design 275
D.2.1 The Infinitesimal Displacement Case 276
D.2.2 The Finite Displacement Case 280
D.3 Practical Aspects of RBF Module Training 283
D.3.1 Finding the Optimal Placement for Each Basis
Function 283
D.3.2 Tuning the Basis Function Width 286
Appendix E Vector Quantization 289
E.I The Generalized Lloyd (K means) Algorithm 289
E.2 Canonical Vector Quantization 290
Appendix F Multidimensional Scaling 291
Appendix G Performance of the Chorus System— Additional
Tables 293
Appendix H Trade Off Between Diagnosticity and Invariance 299
References 303
Index 331
|
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| isbn | 0262050579 |
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| spelling | Edelman, Shimon Verfasser aut Representation and recognition in vision Shimon Edelman Cambridge, Mass. [u.a.] MIT Press 1999 335 S. Ill., graph. Darst. txt rdacontent n rdamedia nc rdacarrier A Bradford book Kategorisierung (DE-588)4163445-7 gnd rswk-swf Visuelle Wahrnehmung (DE-588)4078921-4 gnd rswk-swf Psychologie (DE-588)4047704-6 gnd rswk-swf Visuelle Wahrnehmung (DE-588)4078921-4 s Kategorisierung (DE-588)4163445-7 s Psychologie (DE-588)4047704-6 s DE-604 HBZ Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=008512565&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Edelman, Shimon Representation and recognition in vision Kategorisierung (DE-588)4163445-7 gnd Visuelle Wahrnehmung (DE-588)4078921-4 gnd Psychologie (DE-588)4047704-6 gnd |
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| title | Representation and recognition in vision |
| title_auth | Representation and recognition in vision |
| title_exact_search | Representation and recognition in vision |
| title_full | Representation and recognition in vision Shimon Edelman |
| title_fullStr | Representation and recognition in vision Shimon Edelman |
| title_full_unstemmed | Representation and recognition in vision Shimon Edelman |
| title_short | Representation and recognition in vision |
| title_sort | representation and recognition in vision |
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| topic_facet | Kategorisierung Visuelle Wahrnehmung Psychologie |
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