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Author: Keith William John Anderson
Publisher:
ISBN:
Category :
Languages : en
Pages : 221
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Book Description
Author: Keith William John Anderson
Publisher:
ISBN:
Category :
Languages : en
Pages : 221
Get Book Here
Book Description
Author: Rafael A. Calvo
Publisher: Oxford Library of Psychology
ISBN: 0199942234
Category : Computers
Languages : en
Pages : 625
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Book Description
"The Oxford Handbook of Affective Computing is a definitive reference in the burgeoning field of affective computing (AC), a multidisciplinary field encompassing computer science, engineering, psychology, education, neuroscience, and other disciplines. AC research explores how affective factors influence interactions between humans and technology, how affect sensing and affect generation techniques can inform our understanding of human affect, and on the design, implementation, and evaluation of systems involving affect at their core. The volume features 41 chapters and is divided into five sections: history and theory, detection, generation, methodologies, and applications. Section 1 begins with the making of AC and a historical review of the science of emotion. The following chapters discuss the theoretical underpinnings of AC from an interdisciplinary viewpoint. Section 2 examines affect detection or recognition, a commonly investigated area. Section 3 focuses on aspects of affect generation, including the synthesis of emotion and its expression via facial features, speech, postures, and gestures. Cultural issues are also discussed. Section 4 focuses on methodological issues in AC research, including data collection techniques, multimodal affect databases, formats for the representation of emotion, crowdsourcing techniques, machine learning approaches, affect elicitation techniques, useful AC tools, and ethical issues. Finally, Section 5 highlights applications of AC in such domains as formal and informal learning, games, robotics, virtual reality, autism research, health care, cyberpsychology, music, deception, reflective writing, and cyberpsychology. This compendium will prove suitable for use as a textbook and serve as a valuable resource for everyone with an interest in AC."--
Author: Asit Barman
Publisher: Independent Author
ISBN: 9781805297758
Category :
Languages : en
Pages : 0
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Book Description
When it comes to recognizing facial emotion, the distance feature is extremely important. In the field of affective computing, identifying accurate landmarks is critical as well as a difficult issue. The appearance model detects prominent landmarks on human faces. On the human face, these prominent landmarks form a grid. Distances are calculated within the grid by comparing one landmark point to another. Normalized distances are regarded as a distance signature. To form a normalized shape signature, the possible triangles are found within the grid. Texture characteristics among the landmark points reflected in human faces are important features in facial expression recognition. Appearance-based models detect effective landmarks, and corresponding texture regions are extracted from face images. The texture feature is computed using a Local Binary Pattern (LBP). Normalizing texture signatures is accomplished with the texture feature. A novel concept of corresponding stability indices is introduced, which are eventually discovered to play an important role in facial expression recognition. For these reasons, the stability indices are calculated from each normalized distance, shape, and texture signature feature. To supplement the feature set, individual distance, shape, and texture signature features are used to calculate statistical analyses such as range, moment, skewness, kurtosis, and entropy. The enhanced distance signature feature set is fed into a Multilayer Perceptron (MLP) to generate various expression categories such as anger, sadness, fear, disgust, surprise, and happiness. We train and test our proposed system on four benchmark datasets: Cohn-Kanade (CK+), JAFFE, MMI, and MUG. To categories the expressions, the shape signature feature set is fed into Multilayer Perceptron (MLP) and Nonlinear Auto Regressive with eXogenous (NARX). We tested our proposed system on four databases and found that it outperformed other state-of-the-art solutions. To conduct the experiments, the texture signature feature is used as an input to Nonlinear Auto Regressive with eXogenous (NARX) for recognition of human facial expressions on benchmark datasets, and the results support the effectiveness of the proposed procedure. Following the recognition of expressions using individual signature features, we investigate the combined distance and shape (D-S), distance and texture (D-T), and shape and texture (S-T) signature features. To conduct and validate our experiment and establish its performance superiority over other existing competitors, we feed the combined distance and shape (D-S) feature set into a Multilayer Perceptron (MLP) to categorize the expressions into different categories on four databases. The combined distance-texture (D-T) signature outperforms the distance and texture signatures separately. The effectiveness of the proposed technique based on combined D-T signature is demonstrated by its extremely encouraging performance when compared to other existing arts. To classify the expression on the CK+, JAFFE, MMI, MUG, and Wild face benchmark databases, the combined shape and texture (S-T) features are fed into Multilayer Perceptron (MLP) and Deep Belief Neural (DBN) networks. Extensive testing demonstrates that our proposed methodology outperforms other existing competitors in terms of performance. Finally, the distance signature, shape signature, and texture signature are combined to form a distance-shape-texture signature trio feature for recognizing facial expression. The experimental results also show a promising recognition rate of facial expressions of the distance-shape-texture signature trio when compared to other existing arts.
Author: Amit Konar
Publisher: John Wiley & Sons
ISBN: 1118130669
Category : Technology & Engineering
Languages : en
Pages : 580
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Book Description
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.
Author: Natarajan Meghanathan
Publisher: Springer
ISBN: 3642273173
Category : Computers
Languages : en
Pages : 581
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Book Description
The three volume set LNICST 84 - LNICST 86 constitute the refereed proceedings ofthe Second International Conference on Computer Science and InformationTechnology, CCSIT 2012, held in Bangalore, India, in January 2012. The 55 revised full papers presented in this volume were carefully reviewed andselected from numerous submissions. The papers are organized in topical sectionson advances in computer science and information technology; and ad hoc andubiquitous computing.
Author: Luefeng Chen
Publisher: Springer Nature
ISBN: 3030615774
Category : Technology & Engineering
Languages : en
Pages : 252
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Book Description
This book focuses on the key technologies and scientific problems involved in emotional robot systems, such as multimodal emotion recognition (i.e., facial expression/speech/gesture and their multimodal emotion recognition) and emotion intention understanding, and presents the design and application examples of emotional HRI systems. Aiming at the development needs of emotional robots and emotional human–robot interaction (HRI) systems, this book introduces basic concepts, system architecture, and system functions of affective computing and emotional robot systems. With the professionalism of this book, it serves as a useful reference for engineers in affective computing, and graduate students interested in emotion recognition and intention understanding. This book offers the latest approaches to this active research area. It provides readers with the state-of-the-art methods of multimodal emotion recognition, intention understanding, and application examples of emotional HRI systems.
Author: Namita Gupta
Publisher: John Wiley & Sons
ISBN: 111975058X
Category : Computers
Languages : en
Pages : 576
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Book Description
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.
Author: El Mehdi Bouhabba
Publisher:
ISBN:
Category :
Languages : en
Pages : 230
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Book Description
Enabling computer systems to recognize facial expressions and infer emotions from them in real time presents a challenging research topic. The recognition of emotional information is a key step towards giving computers the ability to interact more naturally and intelligently with people. One of the potential applications of face detection and facial expression recognition is in human computer interfaces. The system will be used for the interaction between human and humanoid robot head, where the detected expression will be mimicked by the robot head. The problem of facial recognition can be divided into two major areas: detection of the face region and identification of the detected region. Detecting human face in computer vision proves to be very challenging due to the fact that human faces can have different forms and colors, adverse lighting conditions, varying angles or view points, scaling differences and different backgrounds. Attempting recognition on an inaccurate detected face region is hopeless. This thesis describes a face detection framework that is capable of processing input images swiftly while achieving high detection rates. The presented face detection system is developed using the response of Haar-Like features and AdaBoost algorithm. A set of experiments in the domain of face detection is presented in this research. The developed system yields face detection performance comparable to the best existing systems, where its accuracy is up to 98%. The face and facial features detected in the video stream are used as input to a Support Vector Machine classifier, which is used for facial expression recognition. The method was evaluated in terms of recognition accuracy for a variety of interaction and classification scenario, and it was proven that the system is able to detect the four expressions successfully. The person-dependent and person-independent experiments demonstrate the effectiveness of a support vector machine to fully automatic and unobtrusive expression recognition in real time.
Author: Ioanna-Ourania Stathopoulou
Publisher: IOS Press
ISBN: 1607505967
Category : Computers
Languages : en
Pages : 268
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Book Description
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."
Author: Thomas B. Moeslund
Publisher: Springer Science & Business Media
ISBN: 0857299972
Category : Computers
Languages : en
Pages : 633
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Book Description
This unique text/reference provides a coherent and comprehensive overview of all aspects of video analysis of humans. Broad in coverage and accessible in style, the text presents original perspectives collected from preeminent researchers gathered from across the world. In addition to presenting state-of-the-art research, the book reviews the historical origins of the different existing methods, and predicts future trends and challenges. Features: with a Foreword by Professor Larry Davis; contains contributions from an international selection of leading authorities in the field; includes an extensive glossary; discusses the problems associated with detecting and tracking people through camera networks; examines topics related to determining the time-varying 3D pose of a person from video; investigates the representation and recognition of human and vehicular actions; reviews the most important applications of activity recognition, from biometrics and surveillance, to sports and driver assistance.
