Computer Perceptual Organization in Computer Vision

By: Kim L. Boyer, Sudeep Sarkar

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Hardcover | 1 July 1994

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Hardcover
252 Pages

Dimensions(cm)
22.86 x 16.51 x 1.91

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This book describes the design of a complete, flexible system for perceptual organization in computer vision using graph theoretic techniques, voting methods, and an extension of the Bayesian networks called perceptual inference networks (PINs). The PIN, which forms the heart of the algorithm, is based on Bayesian probabilistic networks and has potential for being used in other spatial information tasks. The book also has a comprehensive review of the prior work in the area. It not only classifies the prior work but also identifies some areas of future work.

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Non-Fiction Computing & I.T.Computer Science Artificial Intelligence Computer Vision Mathematical Theory of Computation Engineering & Technology Energy Technology & Engineering Electrical Engineering Booktopia Publisher Services World Scientific Publishing

List of Tables
List of Figures
Introduction	p. 1
A Brief History of Perceptual Organisation Research	p. 9
Overview	p. 37
Preattentive Algorithm: Gestalt Graphs and Voting Methods	p. 43
Attentive Algorithm: The Perceptual Inference Network	p. 61
Structuring a Perceptual Inference Network (PIN)	p. 89
Attentive Algorithm: Resource Management	p. 143
Evaluation	p. 163
Conclusion and Future Directions	p. 203
App. A Tutorial for Bayesian Networks	p. 205
References	p. 213
Index	p. 227
Table of Contents provided by Blackwell. All Rights Reserved.

Computer Perceptual Organization in Computer Vision

At a Glance

Hardcover

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How to return your order

Defective items

You Can Find This Book In

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