"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.

Includes bibliographical references and index.

""Title 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 Recognition""""2.1 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 Ekman’s Action Units""; ""3.3 Cultural Variation in Occurrence of Different Aus""

""3.4 Classification Performance Considering Cultural Variability""""3.5 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 Evaluation""""7.5 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""

"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"--

Description based on print version record and CIP data provided by publisher.