Computer vision algorithms for the analysis of video data are
obtained from a camera aimed at the user of an interactive system.
It is potentially useful to enhance the interface between users and
machines. These image sequences provide information from which
machines can identify and keep track of their users, recognize
their facial expressions and gestures, and complement other forms
of human-computer interfaces.
Facial Analysis from Continuous Video with Applications to
Human-Computer Interfaces presents a learning technique based on
information-theoretic discrimination which is used to construct
face and facial feature detectors. This book also describes a
real-time system for face and facial feature detection and tracking
in continuous video. Finally, this book presents a probabilistic
framework for embedded face and facial expression recognition from
image sequences.
Facial Analysis from Continuous Video with Applications to
Human-Computer Interfaces is designed for a professional audience
composed of researchers and practitioners in industry. This book is
also suitable as a secondary text for graduate-level students in
computer science and engineering.
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