Image Understanding
Advances in Computational Vision, Volume Three
Published on 1. May 1990
Book
Hardback
200 pages
978-0-89391-547-6 (ISBN)
Description
The volumes in this series contain studies in computational vision or "image understanding", and explain the computations that underlie the extraction and use of visual information by both biological and artificial systems. Reprints of seminal studies are included along with the original articles.
More details
Language
English
Place of publication
United Kingdom
Publishing group
Intellect
Target group
College/higher education
Professional and scholarly
ISBN-13
978-0-89391-547-6 (9780893915476)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Content
Introduction v
Shimon Ullman
Chapter 1
Computational Vision and Regularization Theory 1
Tomasa Poggio, Vincent Torre, and Christo! Koch
Chapter 2
Boundary Detection by Minimizing Functionals, I 19
D. Mumford and J. Shah
Chapter 3
A Probabilistic Approach to Computational Vision 44
Jose L. Marroquin
Chapter 4
Divide-and-Conquer Techniques for Detecting and Describing
Global Features in Images 80
Azriel Rosenfeld
Chapter 5
Reconstruction of Multidimensional Signals from Zero Crossings 92
Susan R. Curtis and Alan V. Oppenheim
Chapter 6
Image Representation by Reference-Signal Crossings 111
Y.Y Zeevi and S. Shamai (Shitz)
Chapter 7
Accurate Detection of Edges with Large
Laplacian-of-Gaussian Masks 138
Gerard Medioni, Jer-Sen Chen, and Fatih Ulupinar
Chapter 8
Rigidity and Smoothness of Motion: Justifying the Smoothness
Assumption in Motion Measurement 163
A. Yuille and S. Ullman
Chapter 9
Cyclotorsion , Conformal Invariance, and Induced Effects in Stereoscopic
Vision 185
John Parrill, John E.W. Mayhew, and John P. Frisby
Chapter 10
Disparity Gradient, Lipschitz Continuity, and
Computing Binocular Correspondences 197
Stephen B. Pollard, John Porritt, John E.W. Mayhew,
and John P. Frisby
Chapter 11
Color Constancy: A Method for Recovering
Surface Spectral Reflectance 215
Laurence T. Maloney and Brian A. Wandell
Author Index 225
Subject Index 231
Shimon Ullman
Chapter 1
Computational Vision and Regularization Theory 1
Tomasa Poggio, Vincent Torre, and Christo! Koch
Chapter 2
Boundary Detection by Minimizing Functionals, I 19
D. Mumford and J. Shah
Chapter 3
A Probabilistic Approach to Computational Vision 44
Jose L. Marroquin
Chapter 4
Divide-and-Conquer Techniques for Detecting and Describing
Global Features in Images 80
Azriel Rosenfeld
Chapter 5
Reconstruction of Multidimensional Signals from Zero Crossings 92
Susan R. Curtis and Alan V. Oppenheim
Chapter 6
Image Representation by Reference-Signal Crossings 111
Y.Y Zeevi and S. Shamai (Shitz)
Chapter 7
Accurate Detection of Edges with Large
Laplacian-of-Gaussian Masks 138
Gerard Medioni, Jer-Sen Chen, and Fatih Ulupinar
Chapter 8
Rigidity and Smoothness of Motion: Justifying the Smoothness
Assumption in Motion Measurement 163
A. Yuille and S. Ullman
Chapter 9
Cyclotorsion , Conformal Invariance, and Induced Effects in Stereoscopic
Vision 185
John Parrill, John E.W. Mayhew, and John P. Frisby
Chapter 10
Disparity Gradient, Lipschitz Continuity, and
Computing Binocular Correspondences 197
Stephen B. Pollard, John Porritt, John E.W. Mayhew,
and John P. Frisby
Chapter 11
Color Constancy: A Method for Recovering
Surface Spectral Reflectance 215
Laurence T. Maloney and Brian A. Wandell
Author Index 225
Subject Index 231