Human and Machine Vision
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Human and Machine Vision provides information pertinent to an interdisciplinary program of research in visual perception. This book presents a psychophysical study of the human visual system, which provides insights on how to model the flexibility required by a general-purpose visual system. Organized into 17 chapters, this book begins with an overview of how a visual display is segmented into components on the basis of textual differences. This text then proposes three criteria for judging representations of shape. Other chapters consider an increased use of machine vision programs as models of human vision and of data from human vision in developing programs for machine vision. This book discusses as well the diversity and flexibility of systems for representing visual information. The final chapter deals with dot patterns and discusses the process of interring orientation information from collections of them. This book is a valuable resource for psychologists, neurophysiologists, and computer scientists.
Table of Contents
Contributors
Preface
Acknowledgments
A Theory of Textural Segmentation
Criteria for Representations of Shape
Contrasts Between Human and Machine Vision: Should Technology Recapitulate Phylogeny?
Flexibility in Representational Systems
Computing with Connections
Stimulus Information and Processing Mechanisms in Visual Space Perception
Mapping Image Properties into Shape Constraints: Skewed Symmetry, Affine-Transformable Patterns, and the Shape-from-Texture Paradigm
Visual Computation
The Psychology of Perceptual Organization: A Transformational Approach
Why the Human Perceiver Is a Bad Machine
Spatiotemporal Interpolation in Vision
Isolating Representational Systems
A Sketch of a (Computational) Theory of Visual Kinesthesis
Environment-Centered Representation of Spatial Layout: Available Visual Information from Texture and Perspective
Recent Computational Studies in the Interpretation of Structure from Motion
On the Role of Structure in Vision
Computational and Psychophysical Experiments in Grouping: Early Orientation Selection
Product details
- No. of pages: 580
- Language: English
- Copyright: © Academic Press 1983
- Published: December 1, 1983
- Imprint: Academic Press
- eBook ISBN: 9781483266961
About the Editors
Jacob Beck
Barbara Hope
Azriel Rosenfeld
The late Azriel Rosenfeld was a tenured research professor, a distinguished university professor, and the Founding Director of the Center for Automation Research at the University of Maryland in College Park, where he also held affiliate professorships in the departments of computer science, electrical engineering, and psychology. Dr. Rosenfeld was widely regarded as the leading researcher in the world in the field of computer image analysis. Over a period of nearly 40 years, he made fundamental and pioneering contributions to nearly every area of that field. He wrote the first textbook in the field, was founding editor of its first journal, and was co-chairman of its first international conference. He published over 30 books and over 600 book chapters and journal articles, and directed nearly 60 Ph.D. dissertations. Dr. Rosenfeld's research on digital image analysis—specifically on digital geometry and topology and the accurate measurement of statistical features of digital images in the 1960s and 1970s—formed the foundation for a generation of industrial vision inspection systems that have found widespread applications from the automotive to the electronics industry. He was a Fellow of the IEEE and the Washington Academy of Sciences; a Founding Fellow of the AAAI, the ACM, and the IAPR. Among his numerous awards and honors are the IEEE's Emanuel Piore Award, its Third Millennium Medal, and its Distinguished Service Award for Lifetime Achievement in Computer Vision and Pattern Recognition.
Affiliations and Expertise
University of Maryland, College Park, U.S.A.