2D OBJECT DETECTION AND RECOGNITION; Models, Algorithms, and Networks
Language: English
Published by The MIT Press, 2002
- Hardcover
- Used
Seller: Sage Rare & Collectible Books, IOBA, Livonia, MI, U.S.A.Sage Rare & Collectible Books, IOBA
AbeBooks seller since February 28, 2020
Association member: IOBA
Condition: Used - Fine
US$ 175.00
Quantity: 1 available
Add to basketItem description from seller
Black cloth cover with gilt is clean, bright, and in pristine condition. Boards and spine are straight. Binding is tight. Pages are clean and near pristine. Many B&W illustrations. Dust jacket has light shelf rubbing but is in near pristine condition. DJ protected by a brand new, clear, acid-free mylar cover. We add mylar covers to all books with DJs to preserve the DJs and add luster to magnify their beauty. (If pictured, shown without the mylar cover for an accurate representation of dust jacket. ); 336 pages.
Seller Inventory # 22016
- Title
- 2D OBJECT DETECTION AND RECOGNITION; Models, Algorithms, and Networks
- Author
- Yali Amit
- Publisher
- The MIT Press
- Publication year
- 2002
- Condition
- Fine
- Dust jacket
- Near Fine
- Binding
- Hardcover
- Language
- English
- ISBN 10
- 0262011948
- ISBN 13
- 9780262011945
- Seller catalogs
- Engineering, Science
A guide to the computer detection and recognition of 2D objects in gray-level images.
Two important subproblems of computer vision are the detection and recognition of 2D objects in gray-level images. This book discusses the construction and training of models, computational approaches to efficient implementation, and parallel implementations in biologically plausible neural network architectures. The approach is based on statistical modeling and estimation, with an emphasis on simplicity, transparency, and computational efficiency.
The book describes a range of deformable template models, from coarse sparse models involving discrete, fast computations to more finely detailed models based on continuum formulations, involving intensive optimization. Each model is defined in terms of a subset of points on a reference grid (the template), a set of admissible instantiations of these points (deformations), and a statistical model for the data given a particular instantiation of the object present in the image. A recurring theme is a coarse to fine approach to the solution of vision problems. The book provides detailed descriptions of the algorithms used as well as the code, and the software and data sets are available on the Web.
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About the Author
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Sage Rare & Collectible Books, IOBA
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