Energy Minimization Methods in Computer Vision and Pattern Recognition - International Workshop EMMCVPR'97, Venice, Italy, May 21-23, 1997, Proceedings (Paperback, 1997 ed.)


This book constitutes the refereed proceedings of the International Workshop on Energy Minimization Methods in Computer Vision and Pattern Recognition, EMMCVPR'97, held in Venice, Italy, in May 1997.
The book presents 29 revised full papers selected from a total of 62 submissions. Also included are four full invited papers and a keynote paper by leading researchers. The volume is organized in sections on contours and deformable models, Markov random fields, deterministic methods, object recognition, evolutionary search, structural models, and applications. The volume is the first comprehensive documentation of the application of energy minimization techniques in the areas of compiler vision and pattern recognition.

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Product Description

This book constitutes the refereed proceedings of the International Workshop on Energy Minimization Methods in Computer Vision and Pattern Recognition, EMMCVPR'97, held in Venice, Italy, in May 1997.
The book presents 29 revised full papers selected from a total of 62 submissions. Also included are four full invited papers and a keynote paper by leading researchers. The volume is organized in sections on contours and deformable models, Markov random fields, deterministic methods, object recognition, evolutionary search, structural models, and applications. The volume is the first comprehensive documentation of the application of energy minimization techniques in the areas of compiler vision and pattern recognition.

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Product Details

General

Imprint

Springer-Verlag

Country of origin

Germany

Series

Lecture Notes in Computer Science, 1223

Release date

2001

Availability

Expected to ship within 10 - 15 working days

First published

1997

Editors

,

Dimensions

235 x 155 x 29mm (L x W x T)

Format

Paperback

Pages

556

Edition

1997 ed.

ISBN-13

978-3-540-62909-2

Barcode

9783540629092

Categories

LSN

3-540-62909-2



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