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Tables of Contents for Computational Vision
Chapter/Section Title
Page #
Page Count
Preface
xi
I Fundamentals
1
46
Introduction
3
13
Biological information processing
3
4
Information in images
7
6
Vision as information processing
13
3
Imaging
16
31
Intensities
16
8
Imaging systems
24
7
Perspective projection
31
10
Eye movements
41
6
II Contrast, Form, and Color
47
72
Representation and processing of images
49
24
Examples
50
1
Sampling
51
6
Image processing
57
8
Resolution
65
8
Edge detection
73
21
The significance of edges
73
5
Edge detection in one dimension
78
10
Edge detection in two dimensions
88
6
Color and color constancy
94
25
The color of isolated points of light
95
15
Color in images
110
9
III Depth Perception
119
58
Stereoscopic vision
121
25
Differences between images due to parallax
121
3
Stereoscopic geometry (binocular perspective)
124
9
Stereo algorithms
133
8
Neural networks
141
1
Psychophysics
142
4
Shape from shading
146
16
Psychophysics
147
2
Problem statement
149
5
One-dimensional ``images''
154
3
Shape from shading in two dimensions
157
5
Texture and surface orientation
162
15
Texture and texture gradients
162
1
Regular patterns: Vanishing points
163
3
Stochastic patterns 1: Density gradient
166
4
Statistical patterns 2: Shape gradient
170
7
IV Motion
177
66
Motion detection
179
21
Problem statement
179
4
The correlation detector
183
6
The gradient detector
189
6
Orientation in the spatio-temporal image
195
3
Second-order motions
198
2
Optical flow
200
24
Information in the optical flow
200
1
Motion vector fields
201
5
Flow fields for observer motion
206
12
Recovering information from optical flow
218
6
Visual navigation
224
19
Path integration
224
4
Navigation using landmarks
228
8
Constructed environments
236
5
Neurophysiology of spatial memory
241
2
V Appendix
243
2
Glossary of mathematical terms
245
18
Mathematical symbols and units
263
2
Bibliography
265
21
Author Index
286
6
Subject Index
292