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.