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