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Although the history of computer-aided face recognition stretches back to the 1960s, automatic face recognition remains an unsolved problem and still offers a great challenge to computer-vision and pattern recognition researchers. This handbook is a comprehensive account of face recognition research and technology, written by a group of leading international researchers. Twelve chapters cover all the sub-areas and major components for designing operational face recognition systems. Background, modern techniques, recent results, and challenges and future directions are considered. The book is aimed at practitioners and professionals planning to work in face recognition or wanting to become familiar with the state-of- the-art technology. A comprehensive handbook, by leading research authorities, on the concepts, methods, and algorithms for automated face detection and recognition. Essential reference resource for researchers and professionals in biometric security, computer vision, and video image analysis.

Table of Contents (More Detailed TOC)
Introduction (Stan Li, Chinese Academy of Sciences & Anil Jain, Michigan State University)
Face Detection (Stan Li, Microsoft Research Asia)
Modeling Face Shape and Appearance (Tim Cootes & Chris Taylor, Haizhuang Kang & Vladimir Petrovic, University of Manchester)
Parametric Face Modeling and Tracking (Jorgen Ahlberg, Swedish Defense Research Agency & Fadi Dornaika, Linkoping University)
Illumination Modeling for Face Recognition (Ronen Basri, Weizmann Institute of Science & David Jacobs, University of Maryland)
Facial Skin Color Modeling (Birgitta Martinkauppi & Matti Pietikäinen,, University of Oulu)
Face Recognition in Subspaces (Gregory Shakhnarovich, Massachusetts Institute of Technology & Baback Moghaddam, MERL Cambridge Research)
Face Tracking and Recognition from Video (Rama Chellappa, ShaoHua Zhou, University of Maryland)
Face Recognition across Pose and Illumination (Ralph Gross, Simon Baker, Iain Matthews, Takeo Kanade, Carnegie Mellon University)
Morphable Models of Faces (Sami Romdhani, University of Basel & Volker Blanz, Max-Planck-Institut fur Informatik & Curzio Basso & Thomas Vetter, University of Basel)
Facial Expression Analysis (Ying-li Tian, IBM Watson Research Center & Takeo Kanade, Carnegie Mellon University & Jeffrey Cohn, University of Pittsburgh)
Face Synthesis (ZiCheng Liu, Bai-Ning Guo, Microsoft Research)
Face Databases (Ralph Gross, Carnegie Mellon University)
Performance Evaluation (P. Jonathan Phillips, Patrick Grother, Ross Micheals, National Institute of Standards and Technology)
Psychological and Neural Perspectives (Alice J. O'Toole, University of Texas)
Face Recognition Applications (Thomas Huang, Ziyou Xiong, ZhenQiu Zhang, University of Illinois)
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