9781441938909-1441938907-Unconstrained Face Recognition (International Series on Biometrics, 5)

Unconstrained Face Recognition (International Series on Biometrics, 5)

ISBN-13: 9781441938909
ISBN-10: 1441938907
Edition: Softcover reprint of hardcover 1st ed. 2006
Author: Rama Chellappa, Wenyi Zhao, Shaohua Kevin Zhou
Publication date: 2010
Publisher: Springer
Format: Paperback 256 pages
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Book details

ISBN-13: 9781441938909
ISBN-10: 1441938907
Edition: Softcover reprint of hardcover 1st ed. 2006
Author: Rama Chellappa, Wenyi Zhao, Shaohua Kevin Zhou
Publication date: 2010
Publisher: Springer
Format: Paperback 256 pages

Summary

Unconstrained Face Recognition (International Series on Biometrics, 5) (ISBN-13: 9781441938909 and ISBN-10: 1441938907), written by authors Rama Chellappa, Wenyi Zhao, Shaohua Kevin Zhou, was published by Springer in 2010. With an overall rating of 3.6 stars, it's a notable title among other AI & Machine Learning (Information Theory, Computer Science, Graphics & Design, Algorithms, Programming, Graphics & Multimedia, Web Design, Web Development & Design, User Experience & Usability, Security & Encryption) books. You can easily purchase or rent Unconstrained Face Recognition (International Series on Biometrics, 5) (Paperback) from BooksRun, along with many other new and used AI & Machine Learning books and textbooks. And, if you're looking to sell your copy, our current buyback offer is $0.3.

Description

Face recognition has been actively studied over the past decade and continues to be a big research challenge. Just recently, researchers have begun to investigate face recognition under unconstrained conditions. Unconstrained Face Recognition provides a comprehensive review of this biometric, especially face recognition from video, assembling a collection of novel approaches that are able to recognize human faces under various unconstrained situations. The underlying basis of these approaches is that, unlike conventional face recognition algorithms, they exploit the inherent characteristics of the unconstrained situation and thus improve the recognition performance when compared with conventional algorithms. Unconstrained Face Recognition is structured to meet the needs of a professional audience of researchers and practitioners in industry. This volume is also suitable for advanced-level students in computer science.
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