L'anthropologue à l'épreuve du temps

Editorial coordination by Liliane Voyé
Paperback - In French 17.35 €

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Specifications


Publisher
Presses universitaires de Louvain
Title Part
Numéro 2
Editorial coordination by
Liliane Voyé,
Journal
Recherches sociologiques et anthropologiques XXXIII-2002
ISSN
0771677X
Language
French
Publisher Category
Economics and Social Sciences
BISAC Subject Heading
SOC000000 SOCIAL SCIENCE
Onix Audience Codes
06 Professional and scholarly
CLIL (Version 2013-2019)
3081 Sciences sociales
Title First Published
2002
Type of Work
Journal Issue

Paperback


Publication Date
01 January 2006
ISBN-13
9782874630293
Extent
Main content page count : 135
Code
74041
Dimensions
16 x 24 x 0.8 cm
Weight
393 grams
List Price
41.00 €
ONIX XML
Version 2.1, Version 3

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Contents


List of figures

1 Introduction 1

1.1 Context of theWork . . . . . . . . . . . . . . . . . . . . . . . . 1

1.2 Goal and Motivations . . . . . . . . . . . . . . . . . . . . . . . 4

1.3 Targeted Applications . . . . . . . . . . . . . . . . . . . . . . 6

1.4 RelatedWork . . . . . . . . . . . . . . . . . . . . . . . . . . . 7

1.5 Algorithm Overview . . . . . . . . . . . . . . . . . . . . . . . 15

1.5.1 About Silhouette Segmentation . . . . . . . . . . . . . 16

1.6 Thesis Organization . . . . . . . . . . . . . . . . . . . . . . . . 17

2 Intra-Image Feature Extraction 19

2.1 The Crucial Point Set . . . . . . . . . . . . . . . . . . . . . . . 19

2.2 Image Pre-Processing . . . . . . . . . . . . . . . . . . . . . . . 21

2.3 Crucial Point Extraction . . . . . . . . . . . . . . . . . . . . . 21

2.3.1 Geodesic Distance Map Computation . . . . . . . . . 23

Geodesic Distances and Geodesic Maps . . . . . . . . 23

Geodesic Maps Computation . . . . . . . . . . . . . . 25

Center of Gravity . . . . . . . . . . . . . . . . . . . . . 26

2.3.2 Geodesic Distance Map Computation Optimization . 28

2.3.3 Analysis of the Geodesic Distance Function . . . . . . 30

2.3.4 Results . . . . . . . . . . . . . . . . . . . . . . . . . . . 36

2.4 Intra-Image Classification . . . . . . . . . . . . . . . . . . . . 41

2.4.1 Morphological Skeletons . . . . . . . . . . . . . . . . . 41

2.4.2 Selective pruning and robust skeletons . . . . . . . . 44

2.4.3 Feature Classification . . . . . . . . . . . . . . . . . . 45

Holes and Loops . . . . . . . . . . . . . . . . . . . . . 53

2.4.4 Results . . . . . . . . . . . . . . . . . . . . . . . . . . . 57

Morphological Skeletons . . . . . . . . . . . . . . . . . 57

Extraction and Labelling Results . . . . . . . . . . . . 57

2.5 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67

3 Inter-Image Feature Labelling and Tracking 69

3.1 Crucial Point Extraction . . . . . . . . . . . . . . . . . . . . . 69

3.2 Tracking Step . . . . . . . . . . . . . . . . . . . . . . . . . . . 70

3.2.1 Mahalanobis Distance and Gating . . . . . . . . . . . 73

3.2.2 Sequencing versus Global Classification Approach . 75

3.3 Detection Step . . . . . . . . . . . . . . . . . . . . . . . . . . . 76

3.3.1 Prior probability maps . . . . . . . . . . . . . . . . . . 79

3.4 Implementation . . . . . . . . . . . . . . . . . . . . . . . . . . 85

3.5 Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 88

3.5.1 Synthetic results . . . . . . . . . . . . . . . . . . . . . 88

3.5.2 Real segmentation results . . . . . . . . . . . . . . . . 92

General movement range . . . . . . . . . . . . . . . . 92

Possible application: Virtual aerobic home training . 94

Testing the algorithm flexibility. Application: Virtual Tennis game . . . . . . . . . . . . . . . . 96

Testing the algorithm flexibility: Wheelchair user . . 98

Testing the algorithm robustness limits: Segmentation. Application: Gestural navigation . . . 100

Testing the algorithm robustness limits: Challenging postures . . . . . . . . . . . . . . . . . . . . . 102

3.6 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . 104

4 Experimenting with possible extensions and perspectives 107

4.1 Stepping into 3D . . . . . . . . . . . . . . . . . . . . . . . . . 107

4.1.1 Triangulation . . . . . . . . . . . . . . . . . . . . . . . 108

4.1.2 Reliability coefficient . . . . . . . . . . . . . . . . . . . 110

4.1.3 3D Tracking . . . . . . . . . . . . . . . . . . . . . . . . 113

4.1.4 Results . . . . . . . . . . . . . . . . . . . . . . . . . . . 114

4.2 Taking Crucial Points as input for animation . . . . . . . . . 117

4.2.1 Inverse kinematics . . . . . . . . . . . . . . . . . . . . 117

4.2.2 2D animation model . . . . . . . . . . . . . . . . . . . 119

4.2.3 Results . . . . . . . . . . . . . . . . . . . . . . . . . . . 121

5 Conclusion 123

5.1 Conclusions and contributions . . . . . . . . . . . . . . . . . 123

5.2 Publications . . . . . . . . . . . . . . . . . . . . . . . . . . . . 126

5.3 Perspectives . . . . . . . . . . . . . . . . . . . . . . . . . . . . 128

Bibliography 131