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Human Emotion Recognition from Face Images by Paramartha Dutta,Asit Barman Pdf
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.
Advances in Signal Processing and Intelligent Recognition Systems by Sabu M. Thampi,Alexander Gelbukh,Jayanta Mukhopadhyay Pdf
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.
Human-Computer Systems Interaction by Zdzislaw S. Hippe,Juliusz Lech Kulikowski Pdf
For the last decades, as the computer technology has been developing, the importance of human-computer systems interaction problems was growing. This is not only because the computer systems performance characteristics have been im-proved but also due to the growing number of computer users and of their expectations about general computer systems capabilities as universal tools for human work and life facilitation. The early technological problems of man-computer information exchange – which led to a progress in computer programming languages and input/output devices construction – have been step by step dominated by the more general ones of human interaction with-and-through computer systems, shortly denoted as H-CSI problems. The interest of scientists and of any sort specialists to the H-CSI problems is very high as it follows from an increasing number of scientific conferences and publications devoted to these topics. The present book contains selected papers concerning various aspects of H-CSI. They have been grouped into five Parts: I. General H-CSI problems (7 papers), II. Disabled persons helping and medical H-CSI applications (9 papers), III. Psychological and linguistic H-CSI aspects (9 papers), IV. Robots and training systems (8 papers), V. Various H-CSI applications (11 papers).
Facial Analytics for Emotional State Recognition by Konstantinos Papazachariou Pdf
For more than 75 years, social scientists study the human emotions. Whereas numerous theories developed about the provenance and number of basic emotions, most agreed that they could categorize into six categories: angrer, disgust, fear, joy, sadness and surprise. To evaluate emotions, psychologists focused their research in facial expressions analysis. In recent years, the progress in digital technologies field has steered the researchers in psychology, computer science, linguistics, neuroscience, and related disciplines towards the usage of computer systems that analyze and detect the human emotions. Usually, these algorithms are referred in the literature as facial emotion recognition (FER) systems. In this thesis, two different approaches are described and evaluated in order to recognize the six basic emotions automatically from still images.An effective face detection scheme, based on color techniques and the well-known Viola and Jones (VJ) algorithm is proposed for the face and facial characteristics localization within an image. A novel algorithm which exploits the eyes' centers coordinates, is applied on the image to align the detected face. In order to reduce the effects of illumination, homomorphic filtering is applied on the face area. Three regions (mouth, eyes and glabella) are localized and further processed for texture analysis.Although many methods have been proposed in the literature to recognize the emotion from the human face, they are not designed to be able to handle partial occlusions and multiple faces. Therefore, a novel algorithm that extracts information through texture analysis, from each region of interest, is evaluated. Two popular techniques (histograms of oriented gradients and local binary patterns) are utilized to perform texture analysis in the abovementioned facial patches. By evaluating several combinations of their principal parameters and two classification techniques (support vector machine and linear discriminant analysis), three classifiers are proposed. These three models are enabled depending on the regions' availability. Although both classification approaches have shown impressive results, LDA proved to be slightly better especially regarding the amount of data management. Therefore, the final models, which utilized for comparison purpose, were trained using LDA classification.Experiments using Cohn-Kanade plus (CK+) and Amsterdam Dynamic Facial Expression Set (ADFES) datasets demonstrate that the presented FER algorithm has surpassed other significant FER systems in terms of processing time and accuracy. The evaluation of the system involved three experiments: intra-testing experiment (train and test with the same dataset), train/test process between CK+ and ADFES and finally the development of a new database based on selfie-photos, which is tested on the pre-trained models. The last two experiments constitute a certain evidence that Emotion Recognition System (ERS) can operate under various pose and light circumstances.
Face perception is the process by which the brain and mind understand and interpret the face, particularly the human face. The face is an important site for the identification of others and conveys significant social information. Probably because of the importance of its role in social interaction, psychological processes involved in face perception are known to be present from birth, to be complex, and to involve large and widely distributed areas in the brain. These parts of the brain can be damaged to cause a specific impairment in understanding faces known as prosopagnosia. This book presents the latest research in the field.
Smart and Sustainable Intelligent Systems by Namita Gupta,Prasenjit Chatterjee,Tanupriya Choudhury Pdf
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.
Artificial Intelligence Applications and Innovations by Lazaros Iliadis,Ilias Maglogiannis,Harris Papadopoulos Pdf
This book constitutes the refereed proceedings of the 10th IFIP WG 12.5 International Conference on Artificial Intelligence Applications and Innovations, AIAI 2014, held in Rhodes, Greece, in September 2014. The 33 revised full papers and 29 short papers presented were carefully reviewed and selected from numerous submissions. They are organized in the following topical sections: learning-ensemble learning; social media and mobile applications of AI; hybrid-changing environments; agent (AGE); classification pattern recognition; genetic algorithms; image and video processing; feature extraction; environmental AI; simulations and fuzzy modeling; and data mining forecasting.
Emotion Recognition by Amit Konar,Aruna Chakraborty Pdf
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.
Optimization Based Framework for the Classification of Human Emotion in Facial Images by MR C Agilan Pdf
People's daily lives are heavily reliant on communication. When humans communicate with one another, they display a variety of emotions. Recognizing emotions is a fascinating and difficult undertaking. Text, speech, facial expressions, gestures, and biological signals can all be used. Affective computing and technology have grown increasingly crucial in understanding human behavior during the last decade. Patient monitoring, driver fatigue detection, robotics, animation, forensics, medical aid, psychology, surveillance, automotive industry, Human-Robot Interaction for children with autism, situation analysis of social interaction, affective computing, feedback during E-Learning, psychology, contests, and entertainment industries have all benefited from emotion recognition research. Many academics have been driven in recent days to construct an innovative and robust generic and application-specific affective computing system in conjunction with Emotion Intelligence. Emotion is a strong, subjective, and changing feeling state that communicates the importance of good or negative stimuli. The physical cause of emotion origin in the human brain must be investigated. Robots are stimulated in the same way since they are supposed to work in an environment and be able to engage with humans on an emotional level. Important variables include social learning, gesture and natural language communication, emotion perception, and synthesis of interacting partners.
2017IEEE 9th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment and Management (HNICEM) by IEEE Staff Pdf
circuits and systems computing architectures and systems signal processing power and energy biomedical engineering human friendly welfare, industrial, biomedical, agricultural, environmental, educational and entertaining robots intelligent control architectures and methods knowledge based and learning control systems path planning systems reactive multi agent systems machine learning pattern discovery distributed or decentralized control methods intelligent sensors and fusion control actuators building automation artificial intelligence natural language processing neural networks fuzzy logic neuro fuzzy approaches genetic algorithms and evolutionary computing process optimization and techniques wireless communication image and video processing machine vision digital signal processing intelligent data mining analysis, modeling and systems networking client server systems decision support systems information management web development ICT for engineering education
Emotions and Affect in Human Factors and Human-Computer Interaction by Myounghoon Jeon Pdf
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
Visual Affect Recognition by Ioanna-Ourania Stathopoulou Pdf
It is generally known that human faces, as well as body motions and gestures, provide a wealth of information about a person, such as age, race, sex and emotional state. This monograph primarily studies the perception of facial expression of emotion, and secondarily of motion and gestures, with the purpose of developing a fully automated visual affect recognition system for use in modes of human/computer interaction. The book begins with a survey of the literature on emotion perception, followed by a decription of empirical studies conducted with human participants and the construction of a face image database . On the basis of this work, a visual affect recognition system was developed, consisting of two modules: a face detection subsystem and a facia expression recognition subsystem. Details of this system are demonstrated and analyzed, and extensive performance evaluations and test results are provided. Finally, current research avenues leading to visual affect recognition via analysis of body motin and gestures are also discussed."
In the World Library of Psychologists series, international experts themselves present career-long collections of what they judge to be their finest pieces - extracts from books, key articles, salient research findings, and their major theoretical and practical contributions. This volume of self-selected papers recognises Andy Young’s major contribution to the study of face perception, for which he received the BPS Lifetime Achievement Award in 2013. Focusing on his work in facial expression recognition, a specially written introduction gives an overview of his work and contextualises the selection in relation to developments in the field during this time. Divided into five distinct sections, the book covers work on both theoretical and experimental approaches to facial expression recognition, neuropsychology, functional brain imaging, and applications of research. This book will be of great interest to students and researchers of cognitive psychology or neuropsychology interested in face perception. It will also appeal to those with an interest in the highly varied applications of the research and provide insight into a number of clinical disorders.
This volume marks the first time that a collection of contemporary facial scoring techniques and their utility, whether clinical, experimental, theoretical, or otherwise, follows an historical introduction of the area, thereby recording the developmental history of this science.
Face Image Analysis by Unsupervised Learning by Marian Stewart Bartlett Pdf
Face Image Analysis by Unsupervised Learning explores adaptive approaches to image analysis. It draws upon principles of unsupervised learning and information theory to adapt processing to the immediate task environment. In contrast to more traditional approaches to image analysis in which relevant structure is determined in advance and extracted using hand-engineered techniques, Face Image Analysis by Unsupervised Learning explores methods that have roots in biological vision and/or learn about the image structure directly from the image ensemble. Particular attention is paid to unsupervised learning techniques for encoding the statistical dependencies in the image ensemble. The first part of this volume reviews unsupervised learning, information theory, independent component analysis, and their relation to biological vision. Next, a face image representation using independent component analysis (ICA) is developed, which is an unsupervised learning technique based on optimal information transfer between neurons. The ICA representation is compared to a number of other face representations including eigenfaces and Gabor wavelets on tasks of identity recognition and expression analysis. Finally, methods for learning features that are robust to changes in viewpoint and lighting are presented. These studies provide evidence that encoding input dependencies through unsupervised learning is an effective strategy for face recognition. Face Image Analysis by Unsupervised Learning is suitable as a secondary text for a graduate-level course, and as a reference for researchers and practitioners in industry.
