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Markov random field (MRF) theory provides a basis for modeling contextual constraints in visual processing and interpretation. It enables systematic development of optimal vision algorithms when used with optimization principles. This detailed and thoroughly enhanced third edition presents a comprehensive study / reference to theories, methodologies and recent developments in solving computer vision problems based on MRFs, statistics and optimization. It treats various problems in low- and high-level computational vision in a systematic and unified way within the MAP-MRF framework. Among the main issues covered are: how to use MRFs to encode contextual constraints that are indispensable to image understanding; how to derive the objective function for the optimal solution to a problem; and how to design computational algorithms for finding an optimal solution. Easy-to-follow and coherent, the revised edition is accessible, includes the most recent advances, and has new and expanded sections on such topics as: Conditional Random Fields; Discriminative Random Fields; Total Variation (TV) Models; Spatio-temporal Models; MRF and Bayesian Network (Graphical Models); Belief Propagation; Graph Cuts; and Face Detection and Recognition. Features: • Focuses on applying Markov random fields to computer vision problems, such as image restoration and edge detection in the low-level domain, and object matching and recognition in the high-level domain • Introduces readers to the basic concepts, important models and various special classes of MRFs on the regular image lattice, and MRFs on relational graphs derived from images • Presents various vision models in a unified framework, including image restoration and reconstruction, edge and region segmentation, texture, stereo and motion, object matching and recognition, and pose estimation • Uses a variety of examples to illustrate how to convert a specific vision problem involving uncertainties and constraints into essentially an optimization problem under the MRF setting • Studies discontinuities, an important issue in the application of MRFs to image analysis • Examines the problems of model parameter estimation and function optimization in the context of texture analysis and object recognition • Includes an extensive list of references This broad-ranging and comprehensive volume is an excellent reference for researchers working in computer vision, image processing, statistical pattern recognition and applications of MRFs. It is also suitable as a text for advanced courses relating to these areas.

Image processing --Digital techniques --Mathematical models. --- Markov random fields. --- Image processing --- Markov random fields --- Engineering & Applied Sciences --- Applied Physics --- Digital techniques --- Mathematical models --- Mathematical models. --- Fields, Markov random --- Pictorial data processing --- Picture processing --- Processing, Image --- Computer science. --- Computer science --- Image processing. --- Pattern recognition. --- Probabilities. --- Computer Science. --- Image Processing and Computer Vision. --- Pattern Recognition. --- Probability Theory and Stochastic Processes. --- Mathematics of Computing. --- Mathematics. --- Probability --- Statistical inference --- Combinations --- Mathematics --- Chance --- Least squares --- Mathematical statistics --- Risk --- Design perception --- Pattern recognition --- Form perception --- Perception --- Figure-ground perception --- Imaging systems --- Optical data processing --- Computer mathematics --- Discrete mathematics --- Electronic data processing --- Informatics --- Science --- Random fields --- Computer vision. --- Optical pattern recognition. --- Distribution (Probability theory. --- Distribution functions --- Frequency distribution --- Characteristic functions --- Probabilities --- Pattern perception --- Perceptrons --- Visual discrimination --- Machine vision --- Vision, Computer --- Artificial intelligence --- Pattern recognition systems --- Optical data processing. --- Computer science—Mathematics. --- Optical computing --- Visual data processing --- Bionics --- Integrated optics --- Photonics --- Computers --- Optical equipment

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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.

Human face recognition (Computer science) --- Optical pattern recognition. --- Optical data processing --- Pattern perception --- Perceptrons --- Visual discrimination --- Face recognition, Human (Computer science) --- Facial pattern recognition (Computer science) --- Optical pattern recognition --- Computer vision. --- Artificial intelligence. --- Pattern Recognition. --- Computer Imaging, Vision, Pattern Recognition and Graphics. --- Image Processing and 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 --- Pattern recognition. --- Optical data processing. --- Optical computing --- Visual data processing --- Integrated optics --- Photonics --- Computers --- Design perception --- Pattern recognition --- Form perception --- Perception --- Figure-ground perception --- 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

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Biometrics refers to automated methods of recognizing a person based on physiological or behavioral characteristics. The Encyclopedia of Biometrics provides a comprehensive reference to topics in Biometrics, including concepts, modalities, algorithms, devices, systems, security, performance testing, applications and standardization. With an A–Z format, the Encyclopedia of Biometrics provides easy access to relevant information on all aspects of biometrics for those seeking entry into this broad field. The Encyclopedia is composed of approximately 250 overview entries, and 800 definitional entries. Each entry includes a definition, key words, list of synonyms, list of related entries, illustration(s), applications, and a bibliography. Most entries include useful literature references providing the reader with a portal to more detailed information. The style of the entries is expository and tutorial, making the encyclopedia a practical resource for experts in the field and professionals in other fields.

Biometrics (Biology). --- Biometry

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Following the previous four annual conferences, the 5th Chinese Conference on Biometrics Recognition (Sinobiometrics 2004) was held in Guangzhou, China in December 2004. The conference this year was aimed at promoting the international exchange of ideas and providing an opportunity for keeping abreast of the latest developments in biometric algorithms, systems, and applications. The 1st Biometrics Verification Competition (BVC) on face, iris, and fingerprint recognition was also conducted in conjunction with the conference. This book is composed of 74 papers presented at Sinobiometrics 2004, contributed by researchers and industrial practitioners from Korea, Japan, Singapore, Hong Kong, France, UK, US, as well as China. Of these, 60 papers were selected from 140 submissions and 14 were invited. The papers not only presented recent technical advances, but also addressed issues in biometric system design, standardization, and applications. Included among the invited were four feature papers on the ideas and algorithms of the best-performing biometric engines, which were either competition winners at the Face Authentication Test (FAT) 2004 or the Fingerprint Verification Competition (FVC) 2004, or they were the best-performing iris and palmprint recognition algorithms. The papers were complemented by five keynote lectures on biometrics, and face, fingerprint, and iris authentication and multimodal fusion by Arun Ross (West Virginia University) and Anil K. Jain (Michigan State University), Josef Kittler (University of Surrey), John Daugman (University of Cambridge), Raffaele Cappelli (University of Bologna), and Stan Z. Li (Chinese Academy of Sciences).

Biometric identification --- Computer security --- Computer science. --- Special purpose computers. --- Multimedia information systems. --- Pattern recognition. --- Application software. --- Management information systems. --- Computer Science. --- Pattern Recognition. --- Computer Appl. in Social and Behavioral Sciences. --- Computer Appl. in Administrative Data Processing. --- Multimedia Information Systems. --- Special Purpose and Application-Based Systems. --- Management of Computing and Information Systems. --- Computer-based information systems --- EIS (Information systems) --- Executive information systems --- MIS (Information systems) --- Sociotechnical systems --- Information resources management --- Management --- Application computer programs --- Application computer software --- Applications software --- Apps (Computer software) --- Computer software --- Design perception --- Pattern recognition --- Form perception --- Perception --- Figure-ground perception --- Computer-based multimedia information systems --- Multimedia computing --- Multimedia information systems --- Multimedia knowledge systems --- Information storage and retrieval systems --- Special purpose computers --- Computers --- Informatics --- Science --- Communication systems --- Optical pattern recognition. --- Social sciences --- Information systems. --- Multimedia systems. --- Software engineering. --- Information Systems. --- Data processing. --- Computer software engineering --- Engineering --- Optical data processing --- Pattern perception --- Perceptrons --- Visual discrimination --- Seguretat informàtica --- Reconeixement de formes (Informàtica) --- Biometria --- Bioestadística --- Biologia --- Estadística --- Herència (Biologia) --- Anàlisi de supervivència (Biometria) --- Censos --- Genètica quantitativa --- Biomatemàtica --- Estadística matemàtica --- Mostreig (Estadística) --- Autòmats cel·lulars --- Reconeixement automàtic de la parla --- Visió per ordinador --- Informàtica (Seguretat) --- Mesures de seguretat (Informàtica) --- Seguretat (Informàtica) --- Seguretat dels sistemes informàtics --- Sistemes de seguretat --- Protecció de dades --- Control d'accés als ordinadors --- Seguretat de les xarxes d'ordinadors --- Xifratge (Informàtica) --- Pirates informàtics