Author: Konstantinos Papazachariou Publisher: ISBN: Category : Languages : en Pages : 0
Book Description
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.
Author: Flávia de Lima Osório Publisher: ISBN: 9781536152548 Category : Emotion recognition Languages : en Pages : 0
Book Description
This book brings together contributions from different researchers on the theme of facial expressions, with an emphasis on emotional expressions, which may be of interest to professionals in neuroscience, technology and psychopathology. The reader will find theoretical reviews and experimental studies, with different focuses, among them: instruments of measures for use with adults, adolescents and children; training programs to develop emotional competence in children with emotional and behavioral problems, neural and psychophysical aspects associated with the recognition of facial expressions of emotion; emotional contagions, and studies on positive first impressions. Clinical researchers who wish to learn more about and / or update themselves on the subject will benefit from this text.
Author: Amit Konar Publisher: John Wiley & Sons ISBN: 1118130669 Category : Technology & Engineering Languages : en Pages : 580
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: Lazaros Iliadis Publisher: Springer ISBN: 9783662525999 Category : Computers Languages : en Pages : 0
Book Description
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.
Author: Michal Kawulok Publisher: Springer ISBN: 331925958X Category : Technology & Engineering Languages : en Pages : 434
Book Description
This book presents the state-of-the-art in face detection and analysis. It outlines new research directions, including in particular psychology-based facial dynamics recognition, aimed at various applications such as behavior analysis, deception detection, and diagnosis of various psychological disorders. Topics of interest include face and facial landmark detection, face recognition, facial expression and emotion analysis, facial dynamics analysis, face classification, identification, and clustering, and gaze direction and head pose estimation, as well as applications of face analysis.
Author: Paramartha Dutta Publisher: Springer Nature ISBN: 9811538832 Category : Computers Languages : en Pages : 276
Book Description
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.
Author: Nalini K Ratha Publisher: Springer Nature ISBN: 3030746976 Category : Computers Languages : en Pages : 405
Book Description
This book provides an overview of different deep learning-based methods for face recognition and related problems. Specifically, the authors present methods based on autoencoders, restricted Boltzmann machines, and deep convolutional neural networks for face detection, localization, tracking, recognition, etc. The authors also discuss merits and drawbacks of available approaches and identifies promising avenues of research in this rapidly evolving field. Even though there have been a number of different approaches proposed in the literature for face recognition based on deep learning methods, there is not a single book available in the literature that gives a complete overview of these methods. The proposed book captures the state of the art in face recognition using various deep learning methods, and it covers a variety of different topics related to face recognition. This book is aimed at graduate students studying electrical engineering and/or computer science. Biometrics is a course that is widely offered at both undergraduate and graduate levels at many institutions around the world: This book can be used as a textbook for teaching topics related to face recognition. In addition, the work is beneficial to practitioners in industry who are working on biometrics-related problems. The prerequisites for optimal use are the basic knowledge of pattern recognition, machine learning, probability theory, and linear algebra.
Author: Myounghoon Jeon Publisher: Academic Press ISBN: 0128018798 Category : Technology & Engineering Languages : en Pages : 624
Book Description
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
Author: Konstantinos Papazachariou
Author: Flávia de Lima Osório
Author: Amit Konar
Author: Lazaros Iliadis
Author: Michal Kawulok
Author: Paramartha Dutta
Author: Christopher M. Brown
Author: Nalini K Ratha
Author: Myounghoon Jeon
Author: Khin Wee Lai