Machine Learning and Image Interpretation
In this groundbreaking new volume, computer researchers discuss the development of technologies and specific systems that can interpret data with respect to domain knowledge. Although the chapters each illuminate different aspects of image interpretation,
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ADVANCES IN COMPUTER VISION AND MACHINE INTELLIGENCE Series Editor:
Martin D. Levine
McGill University Montreal. Quebec. Canada
COMPUTATIONAL ANALYSIS OF VISUAL MOTION Amar Mitiche COMPUTER VISION FOR ELECTRONICS MANUFACTURING L. F. Pau HUMAN ENGINEERING IN STEREOSCOPIC VIEWING DEVICES Daniel B. Diner and Derek H. Fender MACHINE LEARNING AND IMAGE INTERPRETATION Terry Caelli and Walter F. Bischof PYRAMIDAL ARCHITECTURES FOR COMPUTER VISION Virginio Cantoni and Marco Ferretti SEMANTIC NETWORKS FOR UNDERSTANDING SCENES Gerhard Sagerer and Heinrich Niemann
SIGMA: A Knowledge-Based Aerial Image Understanding System Takahashi Matsuyama and Vincent Shang-Shouq Hwang
A Continuation Order Plan is available for this series. A continuation order will bring delivery of each new volume immediately upon publication. Volumes are billed only upon actual shipment. For further information please contact the publisher.
Machine Learning and Image Interpretation TERRY CAELLI and WALTERF. BISCHOF Curtin University of Technology Perth, Western Australia, Australia
SPRINGER SCIENCE+BUSINESS MEDIA, LLC
Library of Congress Cataloging-in-Publication
Data
Caelli, Terry. Machine learning and image interpretation / Terry Caelli and Walter F . Bischof. p. cm. — (Advances in computer vision and machine inte 11lgence) Includes bibliographical references and index. ISBN 978-1-4899-1818-5 1. Image p r o c e s s i n g — D i g i t a l techniques. 2. Optical pattern recognition. 3. Machine learning. I. Bischof, Walter F . II. Title. III. Series. TA1637.C34 1997 97-36803 006.3'7—dc21 CIP
ISBN 978-1-4899-1818-5 DOI 10.1007/978-1-4899-1816-1
ISBN 978-1-4899-1816-1 (eBook)
© Springer Science+Business Media New York 1997 Originally published by Plenum Press, New York in 1997 Softcover reprint of the hardcover 1st edition 1997 1098765432 1 http://www.plenum.com All rights reserved No part of this book may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, electronic, mechanical, photocopying, microfilming, recording, or otherwise, without written permission from the Publisher
Acknowledgments This work could not have been completed without the support of Curtin University of Technology, the University of Melbourne, the Australian Research Council, National Science and Engineering Research Council of Canada and, finally, but of great importance, families and friends of the research team.
Preface This book represents a six-year effort of the authors and their doctoral students towards developing technologies and specific systems which can interpret image data with respect to domain knowledge. Although each chapter offers a different aspect or perspective to image interpretation, there is one common theme which underpins our approach. That is, image interpretation processes which reflect how humans apply world knowledge to image data must involve perceptual learning in terms of automated knowledge acquisition (induction) and application (deduction and abduction) as well as feedback and consistency checks
