"Written by leaders in the field, this book provides a thorough and insightful presentation of the research methodology on emotion recognition in a highly comprehensive writing style. Topics covered include emotional feature extraction, facial recognition, human-computer interface design, neuro-fuzzy techniques, support vector machine (SVM), reinforcement learning, principal component analysis, the hidden Markov model, and probabilistic models. The result is a innovative edited volume on this timely topic for computer science and electrical engineering students and professionals"-- Provided by publisher
INTERNAL BIBLIOGRAPHIES/INDEXES NOTE
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Includes bibliographical references and index
CONTENTS NOTE
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Introduction to emotion recognition -- Exploiting dynamic dependencies among action units for spontaneous facial action recognition -- Facial expressions : a cross-cultural study -- A subject-dependent facial expression recognition system -- Facial expression recognition using independent component features and hidden Markov model -- Feature selection for facial expression based on rough set theory -- Emotion recognition from facial expressions using type-2 fuzzy sets -- Emotion recognition from non-frontal facial images -- Maximum a posteriori based fusion method for speech emotion recognition -- Emotion recognition in naturalistic speech and language : a survey -- EEG-based emotion recognition using advanced signal processing techniques -- Frequency band localization on multiple physiological signals for human emotion classification using DWT -- Toward affective brain-computer interface : fundamentals and analysis of EEG-based emotion classification -- Bodily expression for automatic affect recognition -- Building a robust system for multimodal emotion recognition -- Semantic audiovisual data fusion for automatic emotion recognition -- A multilevel fusion approach for audiovisual emotion recognition -- From a discrete perspective of emotions to continuous, dynamic, and multimodal affect sensing -- Audiovisual emotion recognition using semi-coupled hidden Markov model with state-based alignment strategy -- Emotion recognition in car industry