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High-level vision : object recognition and visual cognition / Shimon Ullman.

By: Material type: TextTextCopyright date: �1996Description: 1 online resource (xviii, 412 pages) : illustrationsContent type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9780262285353
  • 0262285355
  • 0262210134
  • 9780262210133
  • 0262710072
  • 9780262710077
  • 0585360278
  • 9780585360270
Subject(s): Genre/Form: Additional physical formats: Print version:: High-level vision.DDC classification:
  • 152.14 20
LOC classification:
  • QP475 .U44 1996eb
Online resources:
Contents:
1. Object recognition -- 2. Approaches to object recognition -- 3. The alignment of pictorial descriptions -- 4. The alignment of smooth bounding contours -- 5. Recognition by the combination of views -- 6. Classification -- 7. Image and model correspondence -- 8. Segmentation and saliency -- 9. Visual cognition and visual routines -- 10. Sequence seeking and counter streams : a model for visual cortex -- A. Alignment by features -- B. The curvature method -- C. Errors of the curvature method -- D. Locally affine matching -- E. Definitions.
Summary: 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.
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"A Bradford book."

Includes bibliographical references (pages 383-406) and index.

Print version record.

1. Object recognition -- 2. Approaches to object recognition -- 3. The alignment of pictorial descriptions -- 4. The alignment of smooth bounding contours -- 5. Recognition by the combination of views -- 6. Classification -- 7. Image and model correspondence -- 8. Segmentation and saliency -- 9. Visual cognition and visual routines -- 10. Sequence seeking and counter streams : a model for visual cortex -- A. Alignment by features -- B. The curvature method -- C. Errors of the curvature method -- D. Locally affine matching -- E. Definitions.

English.

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.

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