|
![]() |
|||
|
||||
OverviewFace 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. Full Product DetailsAuthor: Shaohua Kevin Zhou , Rama Chellappa , Wenyi ZhaoPublisher: Springer-Verlag New York Inc. Imprint: Springer-Verlag New York Inc. Edition: 2006 ed. Volume: 5 Dimensions: Width: 15.50cm , Height: 1.50cm , Length: 23.50cm Weight: 1.200kg ISBN: 9780387264073ISBN 10: 0387264078 Pages: 244 Publication Date: 30 November 2005 Audience: College/higher education , Professional and scholarly , Postgraduate, Research & Scholarly , Professional & Vocational Format: Hardback Publisher's Status: Active Availability: In Print ![]() This item will be ordered in for you from one of our suppliers. Upon receipt, we will promptly dispatch it out to you. For in store availability, please contact us. Table of ContentsReviewsAuthor InformationTab Content 6Author Website:Countries AvailableAll regions |