Overview
- Includes an up-to-date survey of unconstrained face recognition
- Professional practitioners of face recognition and other biometrics can use this book as a reference, directly extracting algorithms for their applications
- Includes supplementary material: sn.pub/extras
Part of the book series: International Series on Biometrics (KISB, volume 5)
Access this book
Tax calculation will be finalised at checkout
Other ways to access
Table of contents (12 chapters)
-
Front Matter
-
Fundamentals, Preliminaries and Reviews
-
Front Matter
-
-
Face Recognition Under Variations
-
Front Matter
-
-
Face Recognition Via Kernel Learning
-
Front Matter
-
-
Face Tracking and Recognition from Videos
-
Front Matter
-
-
Summary and Future Research Directions
-
Front Matter
-
-
Back Matter
Keywords
About this book
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.
Authors and Affiliations
Bibliographic Information
Book Title: Unconstrained Face Recognition
Authors: Shaohua Kevin Zhou, Rama Chellappa, Wenyi Zhao
Series Title: International Series on Biometrics
DOI: https://doi.org/10.1007/978-0-387-29486-5
Publisher: Springer New York, NY
eBook Packages: Computer Science, Computer Science (R0)
Copyright Information: Springer-Verlag US 2006
Hardcover ISBN: 978-0-387-26407-3Published: 30 November 2005
Softcover ISBN: 978-1-4419-3890-9Published: 29 November 2010
eBook ISBN: 978-0-387-29486-5Published: 11 October 2006
Edition Number: 1
Number of Pages: XII, 244
Number of Illustrations: 20 b/w illustrations
Topics: Pattern Recognition, Image Processing and Computer Vision, Cryptology, Data Structures and Information Theory, User Interfaces and Human Computer Interaction, Multimedia Information Systems