Face Analysis, Modeling and Recognition Systems

Description

Издательство InTech, 2011, -224 pp.Face recognition represents an important computer vision domain that has been vividly researched in the last decades. Face recognition is a task that the human vision system performs almost effortlessly and successfully, but artificial face recognition represents still a difficult task. The history of the automatic facial recognition area begins in 1960s, but this technology has been propelled into the spotlight by the major advancements in computing capability and research initiatives of the past 20 years. In spite of more than two decades of extensive research, numerous papers being published in prestigious journals and conference volumes in that period, the development of a computer-based artificial facial recognition system having capabilities comparable with those of human vision systems represents an unachieved goal. Artificial face recognition is quite difficult because of many factors, such as viewpoint, lightning conditions, facial expressions, aging effects and occlusions. While humans can recognize easily faces affected by these factors, the computer systems are not even close to this. Face recognition represents both a pattern recognition and biometric domain. As any biometric system, a facial recognition system performs two major operations: person identification and verification. Face identification represents a supervised pattern recognition process performing two other operations: feature extraction and classification respectively. Also, face recognition represents the most popular and the most successful object recognition area. Human face is a physiological biometric identifier widely used in biometric authentication. Face recognition is preferable to many other biometric technologies because of its non-intrusive character and because it is very easy to use. The main application areas of facial recognition are access control, surveillance systems, robotics, human-computer interactions and medical diagnosis. The purpose of this book, entitled Face Analysis, Modeling and Recognition Systems is to provide a concise and comprehensive coverage of artificial face recognition domain across four major areas of interest: biometrics, robotics, image databases and cognitive models. Our book aims to provide the reader with current state-of-the-art in these domains.Part 1 Face Recognition Systems using Principal Component Analysis An Improved Face Recognition System for Service Robot Using Stereo Vision Two Novel Face Recognition Approaches Part 2 Feature-Based Face Detection, Analysis and Recognition Algorithms Face Recognition Using Frequency Domain Feature Extraction Methods Local Feature Based Face Recognition Evaluation of the Facial Paralysis Degree Recognition, Classification and Inversion of Faces in the Multidimensional Space Part 3 Facial Image Database Development: Recognition Evaluation and Security Algorithms A Face Image Database for Evaluating Out-of-Focus Blur Improving Security for Facial Image Using Fragile Digital Watermarking Part 4 Cognitive Models for Face Recognition Disorders Face Recognition in Human: The Roles of Featural and Configurational Processing Psychiatric Disorders of Face Recognition Heritability of Face Recognition New Findings for Face Processing Deficits in the Mental Disorder of Schizophrenia