E-Book Overview
This monograph is an outgrowth of the authors' recent research on the de velopment of algorithms for several low-level vision problems using artificial neural networks. Specific problems considered are static and motion stereo, computation of optical flow, and deblurring an image. From a mathematical point of view, these inverse problems are ill-posed according to Hadamard. Researchers in computer vision have taken the "regularization" approach to these problems, where one comes up with an appropriate energy or cost function and finds a minimum. Additional constraints such as smoothness, integrability of surfaces, and preservation of discontinuities are added to the cost function explicitly or implicitly. Depending on the nature of the inver sion to be performed and the constraints, the cost function could exhibit several minima. Optimization of such nonconvex functions can be quite involved. Although progress has been made in making techniques such as simulated annealing computationally more reasonable, it is our view that one can often find satisfactory solutions using deterministic optimization algorithms.
E-Book Content
Research Notes in Neural Computing
Managing Editor Bart Kosko S. Amari
Editorial Board M. A. Arbib C. von der Malsburg
Advisory Board Y. Abu-Mostafa A. G. Barto E. Bienenstock 1. Cowan M. Cynader W. Freeman G. Gross U. an der Heiden M. Hirsch T. Kohonen 1. W. Moore L. Optic an A. I. Selverston R. Shapley B. Soffer P. Treleaven W. von Seelen B. Widrow S. Zucker
Yi-Tong Zhou
Rama Chellappa
Artificial Neural Networks for Computer Vision With 61 Illustrations
Springer-Verlag New York Berlin Heidelberg London Paris Tokyo Hong Kong Barcelona Budapest
Yi-Tong Zhou HNC, Inc. 5501 Oberlin Drive San Diego, CA 92121, USA
Rama Chellappa Department of Electrical Engineering Center for Automation Research and Institute for Advanced Computer Studies University of Maryland College Park, MD 20742, USA
Managing Editor Bart Kosko Department of Electrical Engineering Signal and Image Processing Institute University of Southern California Los Angeles, CA 90089-2564, USA
Library of Congress Cataloging-in-Publication Data Zhou, Yi-Tong. Artificial neural networks for computer vision 1 Yi-Tong Zhou, Rama Chellappa. p. cm. - (Research notes in neural computing: v.) Includes bibliographical references and index. ISBN-13:978-0-387-97683-9 e-ISBN-13:978-1-4612-2834·9 DOl: 10.1007/978·1·4612·2834·9 1. Neural networks (Computer science) 2. Computer vision. I. Chellappa, Rama. II. Title. III. Series. QA76.87.Z48 1992 006.3-dc20 91-27831
Printed on acid-free paper.
© 1992 Springer· Verlag New York, Inc. All rights reserved. This work may not be translated or copied in whole or in part without the written permission of the publisher (Springer-Verlag New York, Inc., 175 Fifth Avenue, New York, NY 10010, USA), except for brief excerpts in connection with reviews or scholarly analysis. Use in connection with any form of information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed is forbidden. The use of general descriptive names, trade names, trademarks, etc., in this publication, even if the former are not especially identified, is not to be taken as a sign that such names, as understood by the Trade Marks and Merchandise Marks Act, may accordingly be used freely by anyone. Production managed by Christin R. Ciresi; manufacturing supervised by Robert Paella. Camera-ready copy provided by the authors.
987654321 ISBN-13:978-0·387-97683-9
To my wife, Linghong, and my daughters, May and Daisy. Yi-Tong Zhou To my wife, Vishnu Priya, and my son, Vivek. Rama Chellappa
Preface This monograph is an outgrowth of the a