000			03824nam a2200241Ia 4500
003			NULRC
005			20250520102808.0
008			250520s9999 xx 000 0 und d
020			_a9781118130667
040			_cNULRC
050			_aQA 76.9 .E46 2015
100			_aKonar, Amit. _eauthor
245		0	_aEmotion recognition: _ba pattern analysis approach / _cAmit Konar and Aruna Chakraborty.
260			_aHoboken, New Jersey : _bJohn Wiley & Son, Inc., _cc2015
300			_axxxi, 548 pages : _bcolor illustrations ; _c24 cm.
500			_a"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.
504			_aIncludes bibliographical references and index.
505			_aTitle Page -- Copyright -- Dedication -- Preface -- Acknowledgments -- Contributors -- Chapter 1: Introduction to Emotion Recognition -- 1.1 Basics of Pattern Recognition -- 1.2 Emotion Detection as a Pattern Recognition Problem -- 1.3 Feature Extraction -- 1.4 Feature Reduction Techniques -- 1.5 Emotion Classification -- 1.6 Multimodal Emotion Recognition -- 1.7 Stimulus Generation for Emotion Arousal -- 1.8 Validation Techniques -- 1.9 Summary -- References -- Author Biographies Chapter 2: Exploiting Dynamic Dependencies Among Action Units for Spontaneous Facial Action Recognition2.1 Introduction -- 2.2 Related Work -- 2.3 Modeling the Semantic and Dynamic Relationships Among Aus With a DBN -- 2.4 Experimental Results -- 2.5 Conclusion -- References -- Author Biographies -- Note -- Chapter 3: Facial Expressions: A Cross-Cultural Study -- 3.1 Introduction -- 3.2 Extraction of Facial Regions and Ekmanâ€"! Action Units -- 3.3 Cultural Variation in Occurrence of Different Aus 3.4 Classification Performance Considering Cultural Variability3.5 Conclusion -- References -- Author Biographies -- Notes -- Chapter 4: A Subject-dependent Facial Expression Recognition System -- 4.1 Introduction -- 4.2 Proposed Method -- 4.3 Experiment Result -- 4.4 Conclusion -- Acknowledgment -- References -- Author Biographies -- Chapter 5: Facial Expression Recognition Using Independent Component Features and Hidden Markov Model -- 5.1 Introduction -- 5.2 Methodology -- 5.3 Experimental Results -- 5.4 Conclusion -- Acknowledgments 7.4 Fuzzy Type-2 Membership Evaluation7.5 Experimental Details -- 7.6 Performance Analysis -- 7.7 Conclusion -- References -- Author Biographies -- Chapter 8: Emotion Recognition from Non-frontal Facial Images -- 8.1 Introduction -- 8.2 A Brief Review of Automatic Emotional Expression Recognition -- 8.3 Databases for Non-Frontal Facial Emotion Recognition -- 8.4 Recent Advances of Emotion Recognition from Non-Frontal Facial Images -- 8.5 Discussions and Conclusions -- Acknowledgments -- References -- Author Biographies
520			_aThis book provides a comprehensive examination of the research methodology of different modalities of emotion recognition. Key topics of discussion include facial expression, voice and biopotential signal-based emotion recognition. Special emphasis is given to feature selection, feature reduction, classifier design and multi-modal fusion to improve performance of emotion-classifiers.
650			_aHUMAN-COMPUTER INTERACTION
700			_aChakraborty, Aruna _eco-author
942			_2lcc _cBK
999			_c15514 _d15514