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Experiments in the machine interpretation of visual motion

Experiments in the machine interpretation of visual motion (Loan 2 times)

Material type
단행본
Personal Author
Murray, David W. Buxton, Bernard F.
Title Statement
Experiments in the machine interpretation of visual motion / David W. Murray and Bernard F. Buxton.
Publication, Distribution, etc
Cambridge, Mass. :   MIT Press,   1990.  
Physical Medium
236 p. : ill. ; 24 cm.
Series Statement
Artificial intelligence.
ISBN
026213263X
Bibliography, Etc. Note
Includes bibliographical references (p. 215-229) and index.
Subject Added Entry-Topical Term
Computer vision. Motion perception (Vision).
000 00849camuuu200253 a 4500
001 000000919940
005 19990119114745.0
008 900706s1990 maua b 00110 eng
020 ▼a 026213263X
040 ▼a DLC ▼c DLC ▼d DLC ▼d 244002
049 0 ▼l 151024995
050 0 0 ▼a TA1635 ▼b .M87 1990
082 0 0 ▼a 006.3/7 ▼2 20
090 ▼a 006.37 ▼b M981e
100 1 ▼a Murray, David W.
245 1 0 ▼a Experiments in the machine interpretation of visual motion / ▼c David W. Murray and Bernard F. Buxton.
260 ▼a Cambridge, Mass. : ▼b MIT Press, ▼c 1990.
300 ▼a 236 p. : ▼b ill. ; ▼c 24 cm.
490 1 ▼a Artificial intelligence.
504 ▼a Includes bibliographical references (p. 215-229) and index.
650 0 ▼a Computer vision.
650 0 ▼a Motion perception (Vision).
700 1 ▼a Buxton, Bernard F.
830 0 ▼a Artificial intelligence (Cambridge, Mass.)

Holdings Information

No. Location Call Number Accession No. Availability Due Date Make a Reservation Service
No. 1 Location Sejong Academic Information Center/Science & Technology/ Call Number 006.37 M981e Accession No. 151024995 Availability Available Due Date Make a Reservation Service C M

Contents information

Table of Contents


CONTENTS
List of Figures
List of Tables
Preface
1 Image, Scene and Motion = 1
 1.1 Exegesis = 3
 1.2 Scene and image motion = 6
 1.3 Paradigms for computing visual motion = 9
 1.4 Visual versus projected motion = 14
 1.5 Remarks = 20
2 Computing Image Motion = 23
 2.1 Edgels as weak tokens = 23
 2.2 An edgel matching algorithm = 25
 2.3 The algorithm in detail = 26
 2.4 Computer experiments = 32
3 Structure from Motion of Points = 47
 3.1 The aperture problem = 47
 3.2 3D constraints on the aperture problem = 48
 3.3 Point structure from known motion = 51
 3.4 Pointwise depths = 51
 3.5 Straight edges with Known motion = 55
 3.6 Remarks = 58
4 The Structure and Motion of Edges = 61
 4.1 Motion segmentation using edges = 61
 4.2 The Structure from motion algorithm = 68
 4.3 Computer experiments = 70
 4.4 How many edges? = 83
5 From Edges to Surfaces = 85
 5.1 Imposing polyhedral constraints = 85
 5.2 The polyhedral motion algorithm = 92
 5.3 Computer experiments = 94
 5.4 Remarks = 101
6 Structure and Motion of Planes = 103
 6.1 Planar scenes = 103
 6.2 Recovering planar structure and motion = 104
 6.3 Planar facets with known motion = 112
 6.4 3D reconstructions : computer experiments = 112
 6.5 Failures of the planar facet algorithms = 117
 6.6 Reconstructing full visual motion = 121
7 Visual Motion segmentation = 129
 7.1 Global segmentation = 130
 7.2 Local segmentation = 144
 7.3 Remarks = 148
8 Matching to Edge Models = 151
 8.1 Model and data specification = 152
 8.2 Matching in overview = 154
 8.3 The constraints in detail = 157
 8.4 Sign management within search = 165
 8.5 Location stage and testing global validity = 167
 8.6.Computer experiments = 169
 8.7 Remarks = 176
 8.8 Appendix = 177
9 Matching to Planar Surfaces = 181
 9.1 The matching constraints = 181
 9.2 Location stage = 185
 9.3 An experimental example = 185
10 Commentary = 189
 10.1 Sensing, perception and action = 189
 10.2 Representation = 192
 10.3 Computing motion and depth = 195
 10.4 Object recognition and location = 198
 10.5 What next? = 201
 10.6 Perception begets action = 201
 10.7 Dynamic vision = 202
 10.8 Reactive vision = 204
 10.9 Vision and control = 207
 10.10 Recognition = 209
 10.11 Shape and motion = 213
References = 215
Copyright acknowledgements = 231
Index = 233


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