Produktbild: 3D Shape Analysis

3D Shape Analysis Fundamentals, Theory, and Applications

Fr. 169.00

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Produktdetails

Einband

Gebundene Ausgabe

Erscheinungsdatum

07.01.2019

Verlag

John Wiley & Sons Inc

Seitenzahl

368

Maße (L/B/H)

23.5/15.7/2.4 cm

Gewicht

680 g

Sprache

Englisch

ISBN

978-1-119-40510-8

Produktdetails

Einband

Gebundene Ausgabe

Erscheinungsdatum

07.01.2019

Verlag

John Wiley & Sons Inc

Seitenzahl

368

Maße (L/B/H)

23.5/15.7/2.4 cm

Gewicht

680 g

Sprache

Englisch

ISBN

978-1-119-40510-8

Herstelleradresse

Libri GmbH
Europaallee 1
36244 Bad Hersfeld
DE

Email: GPSR Kontakt

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  • Produktbild: 3D Shape Analysis
  • Preface xv
    Acknowledgments xvii

    1 Introduction 1
    1.1 Motivation 1
    1.2 The 3D Shape Analysis Problem 2
    1.3 About This Book 5
    1.4 Notation 9

    Part I Foundations 11

    2 Basic Elements of 3D Geometry and Topology 13
    2.1 Elements of Differential Geometry 13
    2.2 Shape, Shape Transformations, and Deformations 30
    2.3 Summary and Further Reading 38

    3 3D Acquisition and Preprocessing 41
    3.1 Introduction 41
    3.2 3D Acquisition 41
    3.3 Preprocessing 3D Models 56
    3.4 Summary and Further Reading 62

    Part II 3D Shape Descriptors 65

    4 Global Shape Descriptors 67
    4.1 Introduction 67
    4.2 Distribution-Based Descriptors 69
    4.3 View-Based 3D Shape Descriptors 73
    4.4 Spherical Function-Based Descriptors 77
    4.5 Deep Neural Network-Based 3D Descriptors 83
    4.6 Summary and Further Reading 89

    5 Local Shape Descriptors 93
    5.1 Introduction 93
    5.2 Challenges and Criteria 94
    5.3 3D Keypoint Detection 96
    5.4 Local Feature Description 113
    5.5 Feature Aggregation Using Bag of Feature Techniques 126
    5.6 Summary and Further Reading 131

    Part III 3D Correspondence and Registration 135

    6 Rigid Registration 137
    6.1 Introduction 137
    6.2 Coarse Registration 138
    6.3 Fine Registration 152
    6.4 Summary and Further Reading 160

    7 Nonrigid Registration 161
    7.1 Introduction 161
    7.2 Problem Formulation 162
    7.3 Mathematical Tools 165
    7.4 Isometric Correspondence and Registration 168
    7.5 Nonisometric (Elastic) Correspondence and Registration 171
    7.6 Summary and Further Reading 184

    8 Semantic Correspondences 187
    8.1 Introduction 187
    8.2 Mathematical Formulation 188
    8.3 Graph Representation 191
    8.4 Energy Functions for Semantic Labeling 194
    8.5 Semantic Labeling 196
    8.6 Examples 202
    8.7 Summary and Further Reading 204

    Part IV Applications 207

    9 Examples of 3D Semantic Applications 209
    9.1 Introduction 209
    9.2 Semantics: Shape or Status 209
    9.3 Semantics: Class or Identity 212
    9.4 Semantics: Behavior 216
    9.5 Semantics: Position 219
    9.6 Summary and Further Reading 221

    10 3D Face Recognition 223
    10.1 Introduction 223
    10.2 3D Face Recognition Tasks, Challenges and Datasets 224
    10.3 3D Face Recognition Methods 228
    10.4 Summary 239

    11 Object Recognition in 3D Scenes 241
    11.1 Introduction 241
    11.2 Surface Registration-Based Object Recognition Methods 241
    11.3 Machine Learning-Based Object Recognition Methods 255
    11.4 Summary and Further Reading 265

    12 3D Shape Retrieval 267
    12.1 Introduction 267
    12.2 Benchmarks and Evaluation Criteria 270
    12.3 Similarity Measures 275
    12.4 3D Shape Retrieval Algorithms 280
    12.5 Summary and Further Reading 284

    13 Cross-domain Retrieval 285
    13.1 Introduction 285
    13.2 Challenges and Datasets 287
    13.3 Siamese Network for Cross-domain Retrieval 290
    13.4 3D Shape-centric Deep CNN 292
    13.5 Summary and Further Reading 300

    14 Conclusions and Perspectives 301

    References 303
    Index 337