This book constitutes the refereed proceedings of the Third International Workshop on Analysis and Modelling of Faces and Gestures, AMFG 2007, held within the scope of ICCV 2007, the International Conference on Computer Vision. The papers review the status of recognition, analysis and modeling of face, gesture, activity, and behavior. Topics addressed include feature representation, 3D face, video-based face recognition, facial motion analysis, and sign recognition.

During the last 30 years, face recognition and related problems such as face detection/tracking and facial expression recognition have attracted researchers from both the engineering and psychology communities. In addition, extensive research has been carried out to study hand and body gestures. The understanding of how humans perceive these important cues has significant scientific value and extensive applications. For example, human-computer interaction, visual surveillance, and smart video indexing are active application areas. Aiming towards putting such amazing perception capability onto computer systems, researchers have made substantial progress. However, technological challenges still exist in many aspects. Following a format similar to the IEEE International Workshop on Analysis and Modeling of Faces and Gestures (AMFG) 2003, this one-day workshop (AMFG 2005) provided a focused international forum to bring together well-known researchers and research groups to review the status of recognition, analysis and modeling of faces and gestures, to discuss the challenges that we are facing, and to explore future directions. Overall, 30 papers were selected from 90 submitted manuscripts. The topics of these papers range from feature representation, robust recognition, learning, and 3D modeling to psychology. In addition, two invited talks were given, by Prof. Kanade and Dr. Phillips. The technical program was organized into four oral sessions and two poster sessions. This workshop would not have been possible without the timely reviews provided by the members of the Technical Program Committee under a tight schedule. October 2005 Wenyi Zhao Shaogang Gong Xiaoou Tang

Major strides have been made in face processing in the last ten years due to the fast growing need for security in various locations around the globe. A human eye can discern the details of a specific face with relative ease. It is this level of detail that researchers are striving to create with ever evolving computer technologies that will become our perfect mechanical eyes. The difficulty that confronts researchers stems from turning a 3D object into a 2D image. That subject is covered in depth from several different perspectives in this volume. Face Processing: Advanced Modeling and Methods begins with a comprehensive introductory chapter for those who are new to the field. A compendium of articles follows that is divided into three sections. The first covers basic aspects of face processing from human to computer. The second deals with face modeling from computational and physiological points of view. The third tackles the advanced methods, which include illumination, pose, expression, and more. Editors Zhao and Chellappa have compiled a concise and necessary text for industrial research scientists, students, and professionals working in the area of image and signal processing. - Contributions from over 35 leading experts in face detection, recognition and image processing - Over 150 informative images with 16 images in FULL COLOR illustrate and offer insight into the most up-to-date advanced face processing methods and techniques - Extensive detail makes this a need-to-own book for all involved with image and signal processing

The IEEE conference series on Automatic Face and Gesture Recognition is the premier international forum for research in image and video based face, gesture, and body movement recognition Its broad scope includes advances in fundamental computer vision, pattern recognition, computer graphics, and machine learning techniques relevant to face, gesture, and body action, new algorithms, and analysis of specific applications

"This book provides related theoretical background to understand the overall configuration and challenging problem of automated face analysis systems"--Provided by publisher.

A timely book containing foundations and current research directions on emotion recognition by facial expression, voice, gesture and biopotential signals This book provides a comprehensive examination of the research methodology of different modalities of emotion recognition. Key topics of discussion include facial expression, voice and biopotential signal-based emotion recognition. Special emphasis is given to feature selection, feature reduction, classifier design and multi-modal fusion to improve performance of emotion-classifiers. Written by several experts, the book includes several tools and techniques, including dynamic Bayesian networks, neural nets, hidden Markov model, rough sets, type-2 fuzzy sets, support vector machines and their applications in emotion recognition by different modalities. The book ends with a discussion on emotion recognition in automotive fields to determine stress and anger of the drivers, responsible for degradation of their performance and driving-ability. There is an increasing demand of emotion recognition in diverse fields, including psycho-therapy, bio-medicine and security in government, public and private agencies. The importance of emotion recognition has been given priority by industries including Hewlett Packard in the design and development of the next generation human-computer interface (HCI) systems. Emotion Recognition: A Pattern Analysis Approach would be of great interest to researchers, graduate students and practitioners, as the book Offers both foundations and advances on emotion recognition in a single volume Provides a thorough and insightful introduction to the subject by utilizing computational tools of diverse domains Inspires young researchers to prepare themselves for their own research Demonstrates direction of future research through new technologies, such as Microsoft Kinect, EEG systems etc.

Biometrics has moved from using fingerprints to using many methods of assessing human physical and behavioral traits. This guide introduces a new performance evaluation framework designed to offer full coverage of performance evaluation of biometric systems.