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This book discusses human emotion recognition from face images using different modalities, highlighting key topics in facial expression recognition, such as the grid formation, distance signature, shape signature, texture signature, feature selection, classifier design, and the combination of signatures to improve emotion recognition. The book explains how six basic human emotions can be recognized in various face images of the same person, as well as those available from benchmark face image databases like CK+, JAFFE, MMI, and MUG. The authors present the concept of signatures for different characteristics such as distance and shape texture, and describe the use of associated stability indices as features, supplementing the feature set with statistical parameters such as range, skewedness, kurtosis, and entropy. In addition, they demonstrate that experiments with such feature choices offer impressive results, and that performance can be further improved by combining the signatures rather than using them individually. There is an increasing demand for emotion recognition in diverse fields, including psychotherapy, biomedicine, and security in government, public and private agencies. This book offers a valuable resource for researchers working in these areas.
This edited volume contains a selection of refereed and revised papers originally presented at the International Symposium on Signal Processing and Intelligent Recognition Systems (SIRS-2014), March 13-15, 2014, Trivandrum, India. The program committee received 134 submissions from 11 countries. Each paper was peer reviewed by at least three or more independent referees of the program committee and the 52 papers were finally selected. The papers offer stimulating insights into Pattern Recognition, Machine Learning and Knowledge-Based Systems; Signal and Speech Processing; Image and Video Processing; Mobile Computing and Applications and Computer Vision. The book is directed to the researchers and scientists engaged in various field of signal processing and related areas.
A timely book containing foundations and current research directions on emotion recognition by facial expression, voice, gesture and biopotential signals This 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. Written by several experts, the book includes several tools and techniques, including dynamic Bayesian networks, neural nets, hidden Markov model, rough sets, type-2 fuzzy sets, support vector machines and their applications in emotion recognition by different modalities. The book ends with a discussion on emotion recognition in automotive fields to determine stress and anger of the drivers, responsible for degradation of their performance and driving-ability. There is an increasing demand of emotion recognition in diverse fields, including psycho-therapy, bio-medicine and security in government, public and private agencies. The importance of emotion recognition has been given priority by industries including Hewlett Packard in the design and development of the next generation human-computer interface (HCI) systems. Emotion Recognition: A Pattern Analysis Approach would be of great interest to researchers, graduate students and practitioners, as the book Offers both foundations and advances on emotion recognition in a single volume Provides a thorough and insightful introduction to the subject by utilizing computational tools of diverse domains Inspires young researchers to prepare themselves for their own research Demonstrates direction of future research through new technologies, such as Microsoft Kinect, EEG systems etc.
IWBF is an international forum devoted to facilitating synergies in research and development among the areas of biometric recognition, multimedia forensics, forensic biometrics, and forensic science
Filled with breakthrough research, the book explains how to identify the facial expression of basic emotions and how to tell when people try to mask, simulate or neutralize their expression. Features practical exercises to help build skills.
Affect and emotion play an important role in our everyday lives: They are present whatever we do, wherever we are, and wherever we go, without us being aware of them for much of the time. When it comes to interaction, be it with humans, technology, or humans via technology, we suddenly become more aware of emotion, either by seeing the other’s emotional expression, or by not getting an emotional response while anticipating one. Given this, it seems only sensible to explore affect and emotion in human-computer interaction, to investigate the underlying principles, to study the role they play, to develop methods to quantify them, and to finally build applications that make use of them. This is the research field for which, over ten years ago, Rosalind Picard coined the phrase "affective computing". The present book provides an account of the latest work on a variety of aspects related to affect and emotion in human-technology interaction. It covers theoretical issues, user experience and design aspects as well as sensing issues, and reports on a number of affective applications that have been developed in recent years.
Emotions and Affect in Human Factors and Human–Computer Interaction is a complete guide for conducting affect-related research and design projects in H/F and HCI domains. Introducing necessary concepts, methods, approaches, and applications, the book highlights how critical emotions and affect are to everyday life and interaction with cognitive artifacts. The text covers the basis of neural mechanisms of affective phenomena, as well as representative approaches to Affective Computing, Kansei Engineering, Hedonomics, and Emotional Design. The methodologies section includes affect induction techniques, measurement techniques, detection and recognition techniques, and regulation models and strategies. The application chapters discuss various H/F and HCI domains: product design, human–robot interaction, behavioral health and game design, and transportation. Engineers and designers can learn and apply psychological theories and mechanisms to account for their affect-related research and can develop their own domain-specific theory. The approach outlined in this handbook works to close the existing gap between the traditional affect research and the emerging field of affective design and affective computing. - Provides a theoretical background of affective sciences - Demonstrates diverse affect induction methods in actual research settings - Describes sensing technologies, such as brain–computer interfaces, facial expression detection, and more - Covers emotion modeling and its application to regulation processes - Includes case studies and applied examples in a variety of H/F and HCI application areas - Addresses emerging interdisciplinary areas including Positive Technology, Subliminal Perception, Physiological Computing, and Aesthetic Computing
The world is experiencing an unprecedented period of change and growth through all the electronic and technilogical developments and everyone on the planet has been impacted. What was once ‘science fiction’, today it is a reality. This book explores the world of many of once unthinkable advancements by explaining current technologies in great detail. Each chapter focuses on a different aspect - Machine Vision, Pattern Analysis and Image Processing - Advanced Trends in Computational Intelligence and Data Analytics - Futuristic Communication Technologies - Disruptive Technologies for Future Sustainability. The chapters include the list of topics that spans all the areas of smart intelligent systems and computing such as: Data Mining with Soft Computing, Evolutionary Computing, Quantum Computing, Expert Systems, Next Generation Communication, Blockchain and Trust Management, Intelligent Biometrics, Multi-Valued Logical Systems, Cloud Computing and security etc. An extensive list of bibliographic references at the end of each chapter guides the reader to probe further into application area of interest to him/her.
This highly anticipated new edition provides a comprehensive account of face recognition research and technology, spanning the full range of topics needed for designing operational face recognition systems. After a thorough introductory chapter, each of the following chapters focus on a specific topic, reviewing background information, up-to-date techniques, and recent results, as well as offering challenges and future directions. Features: fully updated, revised and expanded, covering the entire spectrum of concepts, methods, and algorithms for automated face detection and recognition systems; provides comprehensive coverage of face detection, tracking, alignment, feature extraction, and recognition technologies, and issues in evaluation, systems, security, and applications; contains numerous step-by-step algorithms; describes a broad range of applications; presents contributions from an international selection of experts; integrates numerous supporting graphs, tables, charts, and performance data.
Original contributions from researchers describing their unpublished research contribution which is not currently under review by another conference or journal and addressing state of the art research are invited to share their work in all areas of Data Science, Machine Learning and its applications but are not limited to Ubiquitous Intelligence and Computing Web Intelligence and Computing Swarm Intelligence Mobile Computing Sensor Networks and Social Sensing Wireless Mesh Networks Wireless Networks Management Wireless Protocols and Architectures Multi Agent Systems Human Computer Interaction Data Mining and Knowledge Discovery Knowledge Management and Networks Data Intensive Computing Architecture Intelligent E Learning Systems Smart Environments and Applications Genetic Algorithms Evolutionary Computation Soft Computing Machine Learning Neural Networks Pattern Recognition Intelligent Control