High-Level Vision

Object Recognition and Visual Cognition
Overview

In this book, Shimon Ullman focuses on the processes of high-level vision that deal with the interpretation and use of what is seen in the image. In particular, he examines two major problems. The first, object recognition and classification, involves recognizing objects despite large variations in appearance caused by changes in viewing position, illumination, occlusion, and object shape. The second, visual cognition, involves the extraction of shape properties and spatial relations in the course of performing visual tasks such as object manipulation, planning movements in the environment, or interpreting graphical material such as diagrams, graphs and maps.

The book first takes up object recognition and develops a novel approach to the recognition of three-dimensional objects. It then studies a number of related issues in high-level vision, including object classification, scene segmentation, and visual cognition. Using computational considerations discussed throughout the book, along with psychophysical and biological data, the final chapter proposes a model for the general flow of information in the visual cortex.

Understanding vision is a key problem in the brain sciences, human cognition, and artificial intelligence. Because of the interdisciplinary nature of the theories developed in this work, High-Level Vision will be of interest to readers in all three of these fields.

Table of Contents

  1. Preface
  2. Acknowledgments
  3. 1. Object Recognition
  4. 2. Approaches to Object Recognition
  5. 3. The Alignment of Pictorial Descriptions
  6. 4. The Alignment of Smooth Bounding Contours
  7. 5. Recognition by the Combination of Views
  8. 6. Classification
  9. 7. Image and Model Correspondence
  10. 8. Segmentation and Saliency
  11. 9. Visual Cognition and Visual Routines
  12. 10. Sequence Seeking and Counter Streams: A Model for Visual Cortex
  13. A. Alignment by Features
  14. B. The Curvature Method
  15. C. Errors of the Curvature Method
  16. D. Locally Affine Matching
  17. E. Definitions
  18. Bibliography
  19. Index