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Increased interest in face recognition stems from rising public concern for safety, the need for identity verification in the digital world, and the need for face analysis and modeling techniques in multimedia data management and computer entertainment.
This authoritative handbook is the first to provide complete coverage of face recognition, including major established approaches, algorithms, systems, databases, evaluation methods, and applications. After a thorough introductory chapter from the editors, 15 chapters address the sub-areas and major components necessary for designing operational face recognition systems. Each chapter focuses on a specific topic, reviewing background information, reviewing up-to-date techniques, presenting results, and offering challenges and future directions.
Features & Benefits:
*Provides comprehensive coverage of the main concepts, including face detection, tracking, alignment, feature extraction, and recognition
*Presents state-of-the-art methods and algorithms for designing face image-processing and recognition systems
*Examines design of secure, accurate, and reliable face recognition systems
*Describes performance evaluation methods and major applications, such as security, person verification, Internet communication, and computer entertainment
*Integrates numerous supporting graphs, tables, charts, and performance data
This accessible, practical reference is an essential resource for scientists and engineers, practitioners, government officials, and students planning to work in image processing, computer vision, biometrics and security, Internet communications, computer graphics, animation, and the computer game industry.
Stan Z. Li leads research programs in face detection and recognition, biometrics, and surveillance at Microsoft and is a senior member of the IEEE. Anil K. Jain is university-distinguished professor in the department of computer science and engineering at Michigan State University, as well as a fellow of the ACM, IEEE, and IAPR.
Key Topics:
Face detection, tracking, and alignment
Performance evaluation
Subspace analysis methods
Illumination and pose modeling
Morphable models of faces
Facial skin-color modeling
Face expression analysis and synthesis
Psychological and neural perspectives
-- Security / Pattern Recognition
-- Intermediate / Advanced
Résumé
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.
Contenu
Face Detection.- Modeling Facial Shape and Appearance.- Parametric Face Modeling and Tracking.- Illumination Modeling for Face Recognition.- Facial Skin Color Modeling.- Color Plates for Chapters 6 and 15.- Face Recognition in Subspaces.- Face Tracking and Recognition from Video.- Face Recognition Across Pose and Illumination.- Morphable Models of Faces.- Facial Expression Analysis.- Face Synthesis.- Face Databases.- Evaluation Methods in Face Recognition.- Psychological and Neural Perspectives on Human Face Recognition.- Face Recognition Applications.