Facial Analysis from Continuous Video with Applications to Human-Computer Interface
Facial Analysis from Continuous Video with Applications to Human-Computer Interface by Antonio J. Colmenarez, published by Springer Science & Business Media on March 31, 2004, spans 134 pages and is presented in English. This book explores computer vision algorithms that analyze video data captured from a camera directed at users of interactive systems, aiming to enhance the interface between users and machines. It discusses how image sequences can provide critical information for machines to identify users, recognize facial expressions, and track gestures, thereby improving human-computer interaction.
Readers will find a detailed examination of a learning technique based on information-theoretic discrimination, which is utilized to develop face and facial feature detectors. The book also describes a real-time system for detecting and tracking faces and facial features in continuous video. Additionally, it introduces a probabilistic framework for recognizing faces and facial expressions from image sequences. This work is intended for a professional audience of researchers and practitioners in the fields of computer science and engineering, and it may serve as a secondary text for graduate-level students.
Official synopsis Publisher
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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