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As a baby one of our earliest stimuli is that of human faces. We rapidly learn to identify, characterize and eventually distinguish those who are near and dear to us. We accept face recognition later as an everyday ability. We realize the complexity of the underlying problem only when we attempt to duplicate this skill in a computer vision system. This book is arranged around a number of clustered themes covering different aspects of face recognition. The first section on Statistical Face Models and Classifiers presents reviews and refinements of some well-known statistical models. The next section presents two articles exploring the use of Infrared imaging techniques and is followed by few articles devoted to refinements of classical methods. New approaches to improve the robustness of face analysis techniques are followed by two articles dealing with real-time challenges in video sequences. A final article explores human perceptual issues of face recognition.

Human face recognition (Computer science) --- Mathematics. --- Math --- Science --- Face recognition, Human (Computer science) --- Facial pattern recognition (Computer science) --- Optical pattern recognition --- Biostatistics --- Physical Sciences --- Engineering and Technology --- Computer and Information Science --- Human-Computer Interaction

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Understanding human activity from video is one of the central problems in the field of computer vision, driven by a wide variety of applications in communications, entertainment, security, commerce, and athletics. This unique text/reference provides a coherent and comprehensive overview of all aspects of video analysis of humans. Broad in coverage and accessible in style, the text presents original perspectives collected from preeminent researchers gathered from across the world. In addition to presenting state-of-the-art research, the book reviews the historical origins of the different existing methods, and predicts future trends and challenges. Topics and features: With a Foreword by Professor Larry Davis of the University of Maryland Institute for Advanced Computer Studies, USA Contains contributions from an international selection of leading authorities in the field Includes an extensive glossary Discusses the problems associated with detecting and tracking people through camera networks Examines topics related to determining the time-varying 3D pose of a person from video Investigates the representation and recognition of human actions Reviews the most important applications of activity recognition, from biometrics and surveillance, to sports and driver assistance With its all-encompassing scope, this essential reference will be of great value not only to graduate students in computer vision, but also to all researchers and professionals interested in systems for the visual analysis of humans. Dr. Thomas B. Moeslund is an Associate Professor in the Department of Architecture, Design &  Media Technology at Aalborg University, Denmark. Dr. Adrian Hilton is Professor and Head of the Visual Media Research Group at the University of Surrey, Guildford, UK. Dr. Volker Krüger is an Associate Professor and Head of the Computer Vision and Machine Intelligence Laboratory at Aalborg University. Dr. Leonid Sigal is a Research Scientist at Disney Research, Pittsburgh, PA USA.

Human face recognition (Computer science). --- Image processing and computer vision. --- Optical pattern recognition. --- Optical pattern recognition --- Human face recognition (Computer science) --- Computer vision --- Human mechanics --- Visual analytics --- Engineering & Applied Sciences --- Electrical & Computer Engineering --- Computer Science --- Applied Physics --- Electrical Engineering --- Biometric identification. --- Image processing --- Digital techniques. --- Digital image processing --- Biometric person authentication --- Biometrics (Identification) --- Computer science. --- Image processing. --- Pattern recognition. --- Computer Science. --- Image Processing and Computer Vision. --- Pattern Recognition. --- Anthropometry --- Identification --- Digital electronics --- Computer vision. --- Optical data processing --- Pattern perception --- Perceptrons --- Visual discrimination --- Machine vision --- Vision, Computer --- Artificial intelligence --- Pattern recognition systems --- Optical data processing. --- Design perception --- Pattern recognition --- Form perception --- Perception --- Figure-ground perception --- Optical computing --- Visual data processing --- Bionics --- Electronic data processing --- Integrated optics --- Photonics --- Computers --- Optical equipment

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The history of computer-aided face recognition dates back to the 1960s, yet the problem of automatic face recognition – a task that humans perform routinely and effortlessly in our daily lives – still poses great challenges, especially in unconstrained conditions. This highly anticipated new edition of the Handbook of Face Recognition provides a comprehensive account of face recognition research and technology, spanning the full range of topics needed for designing operational face recognition systems. After a thorough introductory chapter, each of the following 26 chapters focus on a specific topic, reviewing background information, up-to-date techniques, and recent results, as well as offering challenges and future directions. Topics and features: Fully updated, revised and expanded, covering the entire spectrum of concepts, methods, and algorithms for automated face detection and recognition systems Examines the design of accurate, reliable, and secure face recognition systems Provides comprehensive coverage of face detection, tracking, alignment, feature extraction, and recognition technologies, and issues in evaluation, systems, security, and applications Contains numerous step-by-step algorithms Describes a broad range of applications from person verification, surveillance, and security, to entertainment Presents contributions from an international selection of preeminent experts Integrates numerous supporting graphs, tables, charts, and performance data This practical and authoritative reference is the essential resource for researchers, professionals and students involved in image processing, computer vision, biometrics, security, Internet, mobile devices, human-computer interface, E-services, computer graphics and animation, and the computer game industry. Dr. Stan Z. Li is Professor at the National Laboratory of Pattern Recognition, Director of the Center for Biometrics and Security Research, and Director of the R&D Center for Visual Internet of Things, within the Chinese Academy of Sciences. Dr. Anil K. Jain is University Distinguished Professor in the Department of Computer Science and Engineering at Michigan State University, U.S.A.

Human face recognition (Computer science) --- Electrical & Computer Engineering --- Engineering & Applied Sciences --- Electrical Engineering --- Applied Physics --- Computer Science --- Face recognition, Human (Computer science) --- Facial pattern recognition (Computer science) --- Computer science. --- Artificial intelligence. --- Computer graphics. --- Image processing. --- Pattern recognition. --- Computer Science. --- Pattern Recognition. --- Computer Imaging, Vision, Pattern Recognition and Graphics. --- Image Processing and Computer Vision. --- Artificial Intelligence (incl. Robotics). --- Optical pattern recognition --- Optical pattern recognition. --- Computer vision. --- Artificial Intelligence. --- AI (Artificial intelligence) --- Artificial thinking --- Electronic brains --- Intellectronics --- Intelligence, Artificial --- Intelligent machines --- Machine intelligence --- Thinking, Artificial --- Bionics --- Cognitive science --- Digital computer simulation --- Electronic data processing --- Logic machines --- Machine theory --- Self-organizing systems --- Simulation methods --- Fifth generation computers --- Neural computers --- Machine vision --- Vision, Computer --- Artificial intelligence --- Image processing --- Pattern recognition systems --- Optical data processing --- Pattern perception --- Perceptrons --- Visual discrimination --- Optical data processing. --- Optical computing --- Visual data processing --- Integrated optics --- Photonics --- Computers --- Design perception --- Pattern recognition --- Form perception --- Perception --- Figure-ground perception --- Optical equipment