Multimodal Pattern Recognition Of Social Signals In Human Computer Interaction
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Multimodal Pattern Recognition of Social Signals in Human-Computer-Interaction by Friedhelm Schwenker,Stefan Scherer,Louis-Philippe Morency Pdf
This book constitutes the thoroughly refereed post-workshop proceedings of the Third IAPR TC3 Workshop on Pattern Recognition of Social Signals in Human-Computer-Interaction, MPRSS 2014, held in Stockholm, Sweden, in August 2014, as a satellite event of the International Conference on Pattern Recognition, ICPR 2014. The 14 revised papers presented focus on pattern recognition, machine learning and information fusion methods with applications in social signal processing, including multimodal emotion recognition, user identification, and recognition of human activities.
Multimodal Pattern Recognition of Social Signals in Human-Computer-Interaction by Friedhelm Schwenker,Stefan Scherer Pdf
This book constitutes the refereed post-workshop proceedings of the 5th IAPR TC9 Workshop on Pattern Recognition of Social Signals in Human-Computer-Interaction, MPRSS 2018, held in Beijing, China, in August 2018. The 10 revised papers presented in this book focus on pattern recognition, machine learning and information fusion methods with applications in social signal processing, including multimodal emotion recognition and pain intensity estimation, especially the question how to distinguish between human emotions from pain or stress induced by pain is discussed.
Multimodal Pattern Recognition of Social Signals in Human-Computer-Interaction by Friedhelm Schwenker,Stefan Scherer,Louis-Philippe Morency Pdf
This book constitutes the thoroughly refereed post-workshop proceedings of the First IAPR TC3 Workshop on Pattern Recognition of Social Signals in Human-Computer-Interaction (MPRSS2012), held in Tsukuba, Japan in November 2012, in collaboration with the NLGD Festival of Games. The 21 revised papers presented during the workshop cover topics on facial expression recognition, audiovisual emotion recognition, multimodal Information fusion architectures, learning from unlabeled and partially labeled data, learning of time series, companion technologies and robotics.
Multimodal Pattern Recognition of Social Signals in Human-Computer-Interaction by Friedhelm Schwenker,Stefan Scherer Pdf
This book constitutes the thoroughly refereed post-workshop proceedings of the Fourth IAPR TC9 Workshop on Pattern Recognition of Social Signals in Human-Computer-Interaction, MPRSS 2016, held in Cancun, Mexico, in December 2016. The 13 revised papers presented focus on pattern recognition, machine learning and information fusion methods with applications in social signal processing, including multimodal emotion recognition, user identification, and recognition of human activities.
Multimodal Interface for Human-machine Communication by P. C. Yuen,Yuan Yan Tang,Patrick Shen-pei Wang Pdf
With the advance of speech, image and video technology, human-computer interaction (HCI) will reach a new phase.In recent years, HCI has been extended to human-machine communication (HMC) and the perceptual user interface (PUI). The final goal in HMC is that the communication between humans and machines is similar to human-to-human communication. Moreover, the machine can support human-to-human communication (e.g. an interface for the disabled). For this reason, various aspects of human communication are to be considered in HMC. The HMC interface, called a multimodal interface, includes different types of input methods, such as natural language, gestures, face and handwriting characters.The nine papers in this book have been selected from the 92 high-quality papers constituting the proceedings of the 2nd International Conference on Multimodal Interface (ICMI '99), which was held in Hong Kong in 1999. The papers cover a wide spectrum of the multimodal interface.
Computational Intelligence for Pattern Recognition by Witold Pedrycz,Shyi-Ming Chen Pdf
The book presents a comprehensive and up-to-date review of fuzzy pattern recognition. It carefully discusses a range of methodological and algorithmic issues, as well as implementations and case studies, and identifies the best design practices, assesses business models and practices of pattern recognition in real-world applications in industry, health care, administration, and business. Since the inception of fuzzy sets, fuzzy pattern recognition with its methodology, algorithms, and applications, has offered new insights into the principles and practice of pattern classification. Computational intelligence (CI) establishes a comprehensive framework aimed at fostering the paradigm of pattern recognition. The collection of contributions included in this book offers a representative overview of the advances in the area, with timely, in-depth and comprehensive material on the conceptually appealing and practically sound methodology and practices of CI-based pattern recognition.
Social Signal Processing by Judee K. Burgoon,Nadia Magnenat-Thalmann,Maja Pantic,Alessandro Vinciarelli Pdf
This book provides comprehensive, authoritative surveys covering the modeling, automatic detection, analysis, and synthesis of nonverbal social signals.
Emotion and Stress Recognition Related Sensors and Machine Learning Technologies by Kyandoghere Kyamakya,Fadi Al-Machot,Ahmad Haj Mosa,Hamid Bouchachia,Jean Chamberlain Chedjou,Antoine Bagula Pdf
This book includes impactful chapters which present scientific concepts, frameworks, architectures and ideas on sensing technologies and machine learning techniques. These are relevant in tackling the following challenges: (i) the field readiness and use of intrusive sensor systems and devices for capturing biosignals, including EEG sensor systems, ECG sensor systems and electrodermal activity sensor systems; (ii) the quality assessment and management of sensor data; (iii) data preprocessing, noise filtering and calibration concepts for biosignals; (iv) the field readiness and use of nonintrusive sensor technologies, including visual sensors, acoustic sensors, vibration sensors and piezoelectric sensors; (v) emotion recognition using mobile phones and smartwatches; (vi) body area sensor networks for emotion and stress studies; (vii) the use of experimental datasets in emotion recognition, including dataset generation principles and concepts, quality insurance and emotion elicitation material and concepts; (viii) machine learning techniques for robust emotion recognition, including graphical models, neural network methods, deep learning methods, statistical learning and multivariate empirical mode decomposition; (ix) subject-independent emotion and stress recognition concepts and systems, including facial expression-based systems, speech-based systems, EEG-based systems, ECG-based systems, electrodermal activity-based systems, multimodal recognition systems and sensor fusion concepts and (x) emotion and stress estimation and forecasting from a nonlinear dynamical system perspective. This book, emerging from the Special Issue of the Sensors journal on “Emotion and Stress Recognition Related Sensors and Machine Learning Technologies” emerges as a result of the crucial need for massive deployment of intelligent sociotechnical systems. Such technologies are being applied in assistive systems in different domains and parts of the world to address challenges that could not be addressed without the advances made in these technologies.
The Handbook of Multimodal-Multisensor Interfaces, Volume 2 by Sharon Oviatt,Björn Schuller,Philip Cohen,Daniel Sonntag,Gerasimos Potamianos,Antonio Krüger Pdf
The Handbook of Multimodal-Multisensor Interfaces provides the first authoritative resource on what has become the dominant paradigm for new computer interfaces: user input involving new media (speech, multi-touch, hand and body gestures, facial expressions, writing) embedded in multimodal-multisensor interfaces that often include biosignals. This edited collection is written by international experts and pioneers in the field. It provides a textbook, reference, and technology roadmap for professionals working in this and related areas. This second volume of the handbook begins with multimodal signal processing, architectures, and machine learning. It includes recent deep learning approaches for processing multisensorial and multimodal user data and interaction, as well as context-sensitivity. A further highlight is processing of information about users' states and traits, an exciting emerging capability in next-generation user interfaces. These chapters discuss real-time multimodal analysis of emotion and social signals from various modalities, and perception of affective expression by users. Further chapters discuss multimodal processing of cognitive state using behavioral and physiological signals to detect cognitive load, domain expertise, deception, and depression. This collection of chapters provides walk-through examples of system design and processing, information on tools and practical resources for developing and evaluating new systems, and terminology and tutorial support for mastering this rapidly expanding field. In the final section of this volume, experts exchange views on the timely and controversial challenge topic of multimodal deep learning. The discussion focuses on how multimodal-multisensor interfaces are most likely to advance human performance during the next decade.
Machine Learning Systems for Multimodal Affect Recognition by Markus Kächele Pdf
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.
Multimodal Sentiment Analysis by Soujanya Poria,Amir Hussain,Erik Cambria Pdf
This latest volume in the series, Socio-Affective Computing, presents a set of novel approaches to analyze opinionated videos and to extract sentiments and emotions. Textual sentiment analysis framework as discussed in this book contains a novel way of doing sentiment analysis by merging linguistics with machine learning. Fusing textual information with audio and visual cues is found to be extremely useful which improves text, audio and visual based unimodal sentiment analyzer. This volume covers the three main topics of: textual preprocessing and sentiment analysis methods; frameworks to process audio and visual data; and methods of textual, audio and visual features fusion. The inclusion of key visualization and case studies will enable readers to understand better these approaches. Aimed at the Natural Language Processing, Affective Computing and Artificial Intelligence audiences, this comprehensive volume will appeal to a wide readership and will help readers to understand key details on multimodal sentiment analysis.
Neural Computation in Embodied Closed-Loop Systems for the Generation of Complex Behavior: From Biology to Technology by Poramate Manoonpong,Christian Tetzlaff Pdf
How can neural and morphological computations be effectively combined and realized in embodied closed-loop systems (e.g., robots) such that they can become more like living creatures in their level of performance? Understanding this will lead to new technologies and a variety of applications. To tackle this research question, here, we bring together experts from different fields (including Biology, Computational Neuroscience, Robotics, and Artificial Intelligence) to share their recent findings and ideas and to update our research community. This eBook collects 17 cutting edge research articles, covering neural and morphological computations as well as the transfer of results to real world applications, like prosthesis and orthosis control and neuromorphic hardware implementation.
Innovations in Big Data Mining and Embedded Knowledge by Anna Esposito,Antonietta M. Esposito,Lakhmi C. Jain Pdf
This book addresses the usefulness of knowledge discovery through data mining. With this aim, contributors from different fields propose concrete problems and applications showing how data mining and discovering embedded knowledge from raw data can be beneficial to social organizations, domestic spheres, and ICT markets. Data mining or knowledge discovery in databases (KDD) has received increasing interest due to its focus on transforming large amounts of data into novel, valid, useful, and structured knowledge by detecting concealed patterns and relationships. The concept of knowledge is broad and speculative and has promoted epistemological debates in western philosophies. The intensified interest in knowledge management and data mining stems from the difficulty in identifying computational models able to approximate human behaviors and abilities in resolving organizational, social, and physical problems. Current ICT interfaces are not yet adequately advanced to support and simulate the abilities of physicians, teachers, assistants or housekeepers in domestic spheres. And unlike in industrial contexts where abilities are routinely applied, the domestic world is continuously changing and unpredictable. There are challenging questions in this field: Can knowledge locked in conventions, rules of conduct, common sense, ethics, emotions, laws, cultures, and experiences be mined from data? Is it acceptable for automatic systems displaying emotional behaviors to govern complex interactions based solely on the mining of large volumes of data? Discussing multidisciplinary themes, the book proposes computational models able to approximate, to a certain degree, human behaviors and abilities in resolving organizational, social, and physical problems. The innovations presented are of primary importance for: a. The academic research community b. The ICT market c. Ph.D. students and early stage researchers d. Schools, hospitals, rehabilitation and assisted-living centers e. Representatives from multimedia industries and standardization bodies
Companion Technology by Susanne Biundo,Andreas Wendemuth Pdf
Future technical systems will be companion systems, competent assistants that provide their functionality in a completely individualized way, adapting to a user’s capabilities, preferences, requirements, and current needs, and taking into account both the emotional state and the situation of the individual user. This book presents the enabling technology for such systems. It introduces a variety of methods and techniques to implement an individualized, adaptive, flexible, and robust behavior for technical systems by means of cognitive processes, including perception, cognition, interaction, planning, and reasoning. The technological developments are complemented by empirical studies from psychological and neurobiological perspectives.
New Directions in Behavioral Biometrics by Khalid Saeed Pdf
Automatic biometrics recognition techniques are increasingly important in corporate and public security systems and have increased in methods due to rapid field development. This book discusses classic behavioral biometrics as well as collects the latest advances in techniques, theoretical approaches, and dynamic applications. This future-looking book is an important reference tool for researchers, practitioners, academicians, and technologists. While there are existing books that focus on physiological biometrics or algorithmic approaches deployed in biometrics, this book addresses a gap in the existing literature for a text that is solely dedicated to the topic of behavioral biometrics.