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."

The very significant advances in computer vision and pattern recognition and their applications in the last few years reflect the strong and growing interest in the field as well as the many opportunities and challenges it offers. The second edition of this handbook represents both the latest progress and updated knowledge in this dynamic field. The applications and technological issues are particularly emphasized in this edition to reflect the wide applicability of the field in many practical problems. To keep the book in a single volume, it is not possible to retain all chapters of the first edition. However, the chapters of both editions are well written for permanent reference. This indispensable handbook will continue to serve as an authoritative and comprehensive guide in the field.

Multimodal Behavioral Analysis in the Wild: Advances and Challenges presents the state-of- the-art in behavioral signal processing using different data modalities, with a special focus on identifying the strengths and limitations of current technologies. The book focuses on audio and video modalities, while also emphasizing emerging modalities, such as accelerometer or proximity data. It covers tasks at different levels of complexity, from low level (speaker detection, sensorimotor links, source separation), through middle level (conversational group detection, addresser and addressee identification), and high level (personality and emotion recognition), providing insights on how to exploit inter-level and intra-level links. This is a valuable resource on the state-of-the- art and future research challenges of multi-modal behavioral analysis in the wild. It is suitable for researchers and graduate students in the fields of computer vision, audio processing, pattern recognition, machine learning and social signal processing. - Gives a comprehensive collection of information on the state-of-the-art, limitations, and challenges associated with extracting behavioral cues from real-world scenarios - Presents numerous applications on how different behavioral cues have been successfully extracted from different data sources - Provides a wide variety of methodologies used to extract behavioral cues from multi-modal data

The book Multimedia for Accessible Human Computer Interfaces is to be the first resource to provide in-depth coverage on topical areas of multimedia computing (images, video, audio, speech, haptics, VR/AR, etc.) for accessible and inclusive human computer interfaces. Topics are grouped into thematic areas spanning the human senses: Vision, Hearing, Touch, as well as Multimodal applications. Each chapter is written by different multimedia researchers to provide complementary and multidisciplinary perspectives. Unlike other related books, which focus on guidelines for designing accessible interfaces, or are dated in their coverage of cutting edge multimedia technologies, Multimedia for Accessible Human Computer Interfaces takes an application-oriented approach to present a tour of how the field of multimedia is advancing access to human computer interfaces for individuals with disabilities. Under Theme 1 “Vision-based Technologies for Accessible Human Computer Interfaces”, multimedia technologies to enhance access to interfaces through vision will be presented including: “A Framework for Gaze-contingent Interfaces”, “Sign Language Recognition”, “Fusion-based Image Enhancement and its Applications in Mobile Devices”, and “Open-domain Textual Question Answering Systems”. Under Theme 2 “Auditory Technologies for Accessible Human Computer Interfaces”, multimedia technologies to enhance access to interfaces through hearing will be presented including: “Speech Recognition for Individuals with Voice Disorders” and “Socially Assistive Robots for Storytelling and Other Activities to Support Aging in Place”. Under Theme 3 “Haptic Technologies for Accessible Human Computer Interfaces”, multimedia technologies to enhance access to interfaces through haptics will be presented including: “Accessible Smart Coaching Technologies Inspired by Elderly Requisites” and “Haptic Mediators for Remote Interpersonal Communication”. Under Theme 4 “Multimodal Technologies for Accessible Human Computer Interfaces”, multimedia technologies to enhance access to interfaces through multiple modalities will be presented including: “Human-Machine Interfaces for Socially Connected Devices: From Smart Households to Smart Cities” and “Enhancing Situational Awareness and Kinesthetic Assistance for Clinicians via Augmented-Reality and Haptic Shared-Control Technologies”.

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.

Markus Kächele offers a detailed view on the different steps in the affective computing pipeline, ranging from corpus design and recording over annotation and feature extraction to post-processing, classification of individual modalities and fusion in the context of ensemble classifiers. He focuses on multimodal recognition of discrete and continuous emotional and medical states. As such, specifically the peculiarities that arise during annotation and processing of continuous signals are highlighted. Furthermore, methods are presented that allow personalization of datasets and adaptation of classifiers to new situations and persons.