Suchen und Finden
Foreword
6
Preface
7
Acknowledgements
9
Notation
10
Contents
11
Introduction
15
Part I Geometry: fundamentals of multi-view geometry
19
Geometry prerequisite
20
2.1 Introduction
21
2.2 Projective geometry
21
2.2.1 The basic concepts
21
2.2.2 Projective spaces and transformations
23
2.2.3 Affine and Euclidean specialization
29
2.3 Algebraic geometry
34
2.3.1 The simple methods
34
2.3.2 Ideals, varieties, and Gr¨obner bases
36
2.3.3 Solving polynomial equations with Gr¨obner bases
37
Multi-view geometry
41
3.1 Introduction
42
3.2 The single-view geometry
42
3.2.1 What is a camera?
42
3.2.2 Where is the camera?
47
3.2.3 The DLT calibration
49
3.2.4 The three-point pose algorithm
51
3.3 The uncalibrated two-view geometry
54
3.3.1 The fundamental matrix
55
3.3.2 The seven-point algorithm
57
3.3.3 The eight-point linear algorithm
58
3.4 The calibrated two-view geometry
59
3.4.1 The essential matrix
59
3.4.2 The five-point algorithm
61
3.5 The three-view geometry
65
3.5.1 The trifocal tensor
66
3.5.2 The six-point algorithm
70
3.5.3 The calibrated three views
75
3.6 The N-view geometry
78
3.6.1 The multi-linearities
78
3.6.2 Auto-calibration
80
3.7 Discussions
84
3.8 Bibliographic notes
84
Part II Computation: from pixels to 3D points
86
Feature point
87
4.1 Introduction
88
4.2 Points of interest
88
4.2.1 Tracking features
88
4.2.2 Matching corners
90
4.2.3 Discussions
91
4.3 Scale invariance
92
4.3.1 Invariance and stability
92
4.3.2 Scale, blob and Laplacian
92
4.3.3 Recognizing SIFT
93
4.4 Bibliographic notes
94
Structure from Motion
95
5.1 Introduction
96
5.1.1 Least squares and bundle adjustment
96
5.1.2 Robust statistics and RANSAC
98
5.2 The standard sparse approach
100
5.2.1 A sequence of images
102
5.2.2 A collection of images
103
5.3 The match propagation
104
5.3.1 The best-first match propagation
104
5.3.2 The properties of match propagation
107
5.3.3 Discussions
111
5.4 The quasi-dense approach
113
5.4.1 The quasi-dense resampling
113
5.4.2 The quasi-dense SFM
114
5.4.3 Results and discussions
121
5.5 Bibliographic notes
127
Part III Modeling: from 3D points to objects
129
Surface modeling
130
6.1 Introduction
131
6.2 Minimal surface functionals
132
6.3 A unified functional
133
6.4 Level-set method
133
6.5 A bounded regularization method
134
6.6 Implementation
136
6.7 Results and discussions
138
6.8 Bibliographic notes
145
Hair modeling
146
7.1 Introduction
147
7.2 Hair volume determination
148
7.3 Hair fiber recovery
149
7.3.1 Visibility determination
149
7.3.2 Orientation consistency
150
7.3.3 Orientation triangulation
150
7.4 Implementation
151
7.5 Results and discussions
153
7.6 Bibliographic notes
157
Tree modeling
158
8.1 Introduction
159
8.2 Branche recovery
162
8.2.1 Reconstruction of visible branches
162
8.2.2 Synthesis of occluded branches
164
8.2.3 Interactive editing
166
8.3 Leaf extraction and reconstruction
168
8.3.1 Leaf texture segmentation
168
8.3.2 Graph-based leaf extraction
171
8.3.3 Model-based leaf reconstruction
174
8.4 Results and discussions
176
8.5 Bibliographic notes
183
Fac¸ade modeling
185
9.1 Introduction
186
9.2 Fac¸ade initialization
188
9.2.1 Initial flat rectangle
189
9.2.2 Texture composition
189
9.2.3 Interactive refinement
191
9.3 Fac¸ade decomposition
192
9.3.1 Hidden structure discovery
192
9.3.2 Recursive subdivision
193
9.3.3 Repetitive pattern representation
194
9.3.4 Interactive subdivision refinement
195
9.4 Fac¸ade augmentation
196
9.4.1 Depth optimization
196
9.4.2 Cost definition
198
9.4.3 Interactive depth assignment
198
9.5 Fac¸ade completion
200
9.6 Results and discussions
200
9.7 Bibliographic notes
205
Building modeling
207
10.1 Introduction
208
10.2 Pre-processing
209
10.3 Building segmentation
211
10.3.1 Supervised class recognition
211
10.3.2 Multi-view semantic segmentation
213
10.4 Building partition
215
10.4.1 Global vertical alignment
216
10.4.2 Block separator
216
10.4.3 Local horizontal alignment
217
10.5 Fac¸ade modeling
218
10.5.1 Inverse orthographic composition
219
10.5.2 Structure analysis and regularization
221
10.5.3 Repetitive pattern rediscovery
224
10.5.4 Boundary regularization
225
10.6 Post-processing
226
10.7 Results and discussions
227
10.8 Bibliographic notes
232
List of Algorithms
234
List of Figures
235
References
243
Index
255
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