Computer vision algorithms for analyzing video data are obtained from a camera focused on the user of an interactive system. Machines can use these image sequences to identify and keep track of their users, recognize their facial expressions and gestures, and complement other forms of human-computer interfaces. This book presents a learning technique based on information-theoretic discrimination, used to construct face and facial feature detectors. It also describes a real-time system for face and facial feature detection and tracking in continuous video, and presents a probabilistic framework for embedded face and facial expression recognition from image sequences.

Presents a learning technique based on information-theoretic discrimination which is used to construct face and facial feature detectors Describes a real-time system for face and facial feature detection and tracking in continuous video Presents a probabilistic framework for embedded face and facial expression recognition from image sequences

Inhalt
Information-based Maximum Discrimination.- Face and Facial Feature Detection.- Face and Facial Feature Tracking.- Face and Facial Expression Recognition.- 3-D Model-based Image Communication.- Implementations, Experiments and Results.- Application in an Audio-visual Person Recognition System.- Conclusions.