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Deadline extended: CBAR@FG 2019 CFP: 6th International Workshop on Context Based Affect Recognition

by zakia hammal

Apologies for cross-posting *********************************************************************************** CBAR 2019: CALL FOR PAPERS 6th International Workshop on CONTEXT BASED AFFECT RECOGNITION https://cbar2019.blogspot.com/ Submission Deadline: January 28th, 2019 (Extended) *********************************************************************************** The 6th International Workshop on Context Based Affect Recognition (CBAR 2019) will be held in conjunction with FG 2019 in May 2019 in Lille France – http://fg2019.org/ For details concerning the workshop program, paper submission, and guidelines please visit our workshop website at: https://cbar2019.blogspot.com/ Best regards, Zakia Hammal Zakia Hammal, PhD The Robotics Institute, Carnegie Mellon University http://www.ri.cmu.edu/ http://ri.cmu.edu/personal-pages/ZakiaHammal/

5 years, 11 months

LIRIS Children Spontaneous Facial Expression Video Database (LIRIS-CSE)

by Rizwan Ahmed Khan

Dear members, We are pleased to announce publication of first of its kind children spontaneous facial expression video database, the LIRIS Children Spontaneous Facial Expression Video Database (LIRIS-CSE). This unique database contains spontaneous / natural facial expressions of 12 children in diverse settings with variable recording scenarios showing six universal or prototypic emotional expressions (happiness, sadness, anger, surprise, disgust and fear). Children are recorded in constraint free environment (no restriction on head movement, no restriction on hands movement, free sitting setting, no restriction of any sort) while they watched specially built / selected stimuli. This constraint free environment allowed us to record spontaneous / natural expression of children as they occur. The database has been validated by 22 human raters. Details of the database are presented in the following publication: A novel database of Children's Spontaneous Facial Expressions (LIRIS-CSE). Rizwan Ahmed Khan, Crenn Arthur, Alexandre Meyer, Saida Bouakaz. arXiv (2018) preprint, arXiv:1812.01555. https://arxiv.org/abs/1812.01555 To request database download (for research purpose only) visit project webpage at: https://childrenfacialexpression.projet.liris.cnrs.fr/ __________________ Best Regards, Dr. Rizwan Ahmed KHAN Associate Professor, Barrett Hodgson University, Karachi, Pakistan. || Researcher - Laboratoire d'InfoRmatique en Image et Systèmes d'information (LIRIS), Lyon, France. <https://sites.google.com/site/drkhanrizwan17/> <http://scholar.google.com/citations?user=T66djn8AAAAJ&hl=en> <http://dblp.uni-trier.de/pers/hd/k/Khan:Rizwan_Ahmed.html> <https://www.youtube.com/user/Rizwankhan2000/videos?view_as=subscriber> *Help preserve the color of our world – Think before you print.*

5 years, 11 months

CBAR@FG 2019 CFP: 6th International Workshop on Context Based Affect Recognition @ FG 2019

by zakia hammal

Apologies for cross-posting *********************************************************************************** CBAR 2019: CALL FOR PAPERS 6th International Workshop on CONTEXT BASED AFFECT RECOGNITION https://cbar2019.blogspot.com/ Submission Deadline: January 7th, 2019 *********************************************************************************** The 6th International Workshop on Context Based Affect Recognition (CBAR 2019) will be held in conjunction with FG 2019 in May 2019 in Lille France – http://fg2019.org/ For details concerning the workshop program, paper submission, and guidelines please visit our workshop website at: https://cbar2019.blogspot.com/ Best regards, Zakia Hammal Zakia Hammal, PhD The Robotics Institute, Carnegie Mellon University http://www.ri.cmu.edu/ http://ri.cmu.edu/personal-pages/ZakiaHammal/

5 years, 11 months

CFP: TAC | Special Issue on Automated Perception of Human Affect from Longitudinal Behavioral Data

by Pablo Barros

CALL FOR PAPERS Extended Deadline for the IEEE Transactions on Affective Computing Special Issue on Automated Perception of Human Affect from Longitudinal Behavioral Data Website: https://www2.informatik.uni-hamburg.de/wtm/omgchallenges/tacSpecialIssue201… I. Aim and Scope Research trends within artificial intelligence and cognitive sciences are still heavily based on computational models that attempt to imitate human perception in various behavior categorization tasks. However, most of the research in the field focuses on instantaneous categorization and interpretation of human affect, such as the inference of six basic emotions from face images, and/or affective dimensions (valence-arousal), stress and engagement from multi-modal (e.g., video, audio, and autonomic physiology) data. This diverges from the developmental aspect of emotional behavior perception and learning, where human behavior and expressions of affect evolve and change over time. Moreover, these changes are present not only in the temporal domain but also within different populations and more importantly, within each individual. This calls for a new perspective when designing computational models for analysis and interpretation of human affective behaviors: the computational models that can timely and efficiently adapt to different contexts and individuals over time, and also incorporate existing neurophysiological and psychological findings (prior knowledge). Thus, the long-term goal is to create life-long personalized learning and inference systems for analysis and perception of human affective behaviors. Such systems would benefit from long-term contextual information (including demographic and social aspects) as well as individual characteristics. This, in turn, would allow building intelligent agents (such as mobile and robot technologies) capable of adapting their behavior in a continuous and on-line manner to the target contexts and individuals. This special issue aims at contributions from computational neuroscience and psychology, artificial intelligence, machine learning, and affective computing, challenging and expanding current research on interpretation and estimation of human affective behavior from longitudinal behavioral data, i.e., single or multiple modalities captured over extended periods of time allowing efficient profiling of target behaviors and their inference in terms of affect and other socio-cognitive dimensions. We invite contributions focusing on both the theoretical and modeling perspective, as well as applications ranging from human-human, human-computer and human-robot interactions. II. Potential Topics Given computational models, the capability to perceive and understand emotion behavior is an important and popular research topic. That is why recent special issues on the IEEE Journal on Transactions on Affective Computing covered topics from emotion behavior analysis “in-the-wild” to personality analysis. However, most of the research published by these specific calls treat emotion behavior as an instantaneous event, relating mostly to emotion recognition, and thus neglect the development of complex emotion behavior models. Our special issue will foster the development of the field by focusing excellent research on emotion models for long-term behavior analysis. The topics of interest for this special issue include, but are not limited to: - New theories and findings on continuous emotion recognition - Multi- and Cross-modal emotion perception and interpretation - Lifelong affect analysis, perception, and interpretation - Novel neural network models for affective processing - New neuroscientific and psychological findings on continuous emotion representation - Embodied artificial agents for empathy and emotion appraisal - Machine learning for affect-driven interventions - Socially intelligent human-robot interaction - Personalized systems for human affect recognition III. Submission Prospective authors are invited to submit their manuscripts electronically, adhering to the IEEE Transactions on Affective Computing guidelines ( https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=5165369). Please submit your papers through the online system ( https://mc.manuscriptcentral.com/taffc-cs) and be sure to select the special issue: Special Issue/Section on Automated Perception of Human Affect from Longitudinal Behavioral Data. IV. IMPORTANT DATES: Submissions Deadline: 15th of February 2019 V. Guest Editors Pablo Barros, University of Hamburg, Germany Stefan Wermter, University of Hamburg, Germany Ognjen (Oggi) Rudovic, Massachusetts Institute of Technology, United States of America Hatice Gunes, University of Cambridge, United Kingdom -- Dr. Pablo Barros Postdoctoral Research Associate - Crossmodal Learning Project (CML) Knowledge Technology Department of Informatics University of Hamburg Vogt-Koelln-Str. 30 22527 Hamburg, Germany Phone: +49 40 42883 2535 Fax: +49 40 42883 2515 barros at informatik.uni-hamburg.dehttp://www.pablobarros.nethttps://www.inf.uni-hamburg.de/en/inst/ab/wtm/people/barros.htmlhttps://www.inf.uni-hamburg.de/en/inst/ab/wtm/

5 years, 11 months

CFP: TAC | Special Issue on Automated Perception of Human Affect from Longitudinal Behavioral Data

by Pablo Barros

CALL FOR PAPERS IEEE Transactions on Affective Computing Special Issue on Automated Perception of Human Affect from Longitudinal Behavioral Data Website: https://www2.informatik.uni-hamburg.de/wtm/omgchallenges/tacSpecialIssue201… I. Aim and Scope Research trends within artificial intelligence and cognitive sciences are still heavily based on computational models that attempt to imitate human perception in various behavior categorization tasks. However, most of the research in the field focuses on instantaneous categorization and interpretation of human affect, such as the inference of six basic emotions from face images, and/or affective dimensions (valence-arousal), stress and engagement from multi-modal (e.g., video, audio, and autonomic physiology) data. This diverges from the developmental aspect of emotional behavior perception and learning, where human behavior and expressions of affect evolve and change over time. Moreover, these changes are present not only in the temporal domain but also within different populations and more importantly, within each individual. This calls for a new perspective when designing computational models for analysis and interpretation of human affective behaviors: the computational models that can timely and efficiently adapt to different contexts and individuals over time, and also incorporate existing neurophysiological and psychological findings (prior knowledge). Thus, the long-term goal is to create life-long personalized learning and inference systems for analysis and perception of human affective behaviors. Such systems would benefit from long-term contextual information (including demographic and social aspects) as well as individual characteristics. This, in turn, would allow building intelligent agents (such as mobile and robot technologies) capable of adapting their behavior in a continuous and on-line manner to the target contexts and individuals. This special issue aims at contributions from computational neuroscience and psychology, artificial intelligence, machine learning, and affective computing, challenging and expanding current research on interpretation and estimation of human affective behavior from longitudinal behavioral data, i.e., single or multiple modalities captured over extended periods of time allowing efficient profiling of target behaviors and their inference in terms of affect and other socio-cognitive dimensions. We invite contributions focusing on both the theoretical and modeling perspective, as well as applications ranging from human-human, human-computer and human-robot interactions. II. Potential Topics Given computational models, the capability to perceive and understand emotion behavior is an important and popular research topic. That is why recent special issues on the IEEE Journal on Transactions on Affective Computing covered topics from emotion behavior analysis “in-the-wild” to personality analysis. However, most of the research published by these specific calls treat emotion behavior as an instantaneous event, relating mostly to emotion recognition, and thus neglect the development of complex emotion behavior models. Our special issue will foster the development of the field by focusing excellent research on emotion models for long-term behavior analysis. The topics of interest for this special issue include, but are not limited to: - New theories and findings on continuous emotion recognition - Multi- and Cross-modal emotion perception and interpretation - Lifelong affect analysis, perception, and interpretation - Novel neural network models for affective processing - New neuroscientific and psychological findings on continuous emotion representation - Embodied artificial agents for empathy and emotion appraisal - Machine learning for affect-driven interventions - Socially intelligent human-robot interaction - Personalized systems for human affect recognition III. Submission Prospective authors are invited to submit their manuscripts electronically, adhering to the IEEE Transactions on Affective Computing guidelines ( https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=5165369). Please submit your papers through the online system ( https://mc.manuscriptcentral.com/taffc-cs) and be sure to select the special issue: Special Issue/Section on Automated Perception of Human Affect from Longitudinal Behavioral Data. IV. IMPORTANT DATES: Submissions Deadline: 15th of February 2019 V. Guest Editors Pablo Barros, University of Hamburg, Germany Stefan Wermter, University of Hamburg, Germany Ognjen (Oggi) Rudovic, Massachusetts Institute of Technology, United States of America Hatice Gunes, University of Cambridge, United Kingdom -- Best regards, *Pablo Barros* *http://www.pablobarros.net <http://www.pablobarros.net>*

5 years, 11 months

ICMI 2019: Call for Long and Short Papers

by zakia hammal

Apologies for cross-posting *********************************************************************************** ICMI 2019: Call for Long and Short Papers https://icmi.acm.org/2019/index.php?id=cfp Abstract Submission: May 1, 2019 (11:59pm PST) Final Submission: May 7, 2019 (11:59pm PST) *********************************************************************************** Call for Long and Short Papers The 21st International Conference on Multimodal Interaction (ICMI 2019) will be held in Suzhou, China. ICMI is the premier international forum for multidisciplinary research on multimodal human-human and human-computer interaction, interfaces, and system development. The conference focuses on theoretical and empirical foundations, component technologies, and combined multimodal processing techniques that define the field of multimodal interaction analysis, interface design, and system development. We are keen to showcase novel input and output modalities and interactions to the ICMI community. ICMI 2019 will feature a single-track main conference which includes: keynote speakers, technical full and short papers (including oral and poster presentations), demonstrations, exhibits and doctoral spotlight papers. The conference will also feature workshops and grand challenges. The proceedings of ICMI 2019 will be published by ACM as part of their series of International Conference Proceedings and Digital Library. We also want to welcome conference papers from behavioral and social sciences. These papers allow us to understand how technology can be used to increase our scientific knowledge and may focus less on presenting technical or algorithmic novelty. For this reason, the "novelty" criteria used during ICMI 2019 review will be based on two sub-criteria (i.e., scientific novelty and technical novelty as described below). Accepted papers at ICMI 2019 only need to be novel on one of these sub-criteria. In other words, a paper which is strong on scientific knowledge contribution but low on algorithmic novelty should be ranked similarly to a paper that is high on algorithmic novelty but low on knowledge discovery. Scientific Novelty: Papers should bring some new knowledge to the scientific community. For example, discovering new behavioral markers that are predictive of mental health or how new behavioral patterns relate to children’s interactions during learning. It is the responsibility of the authors to perform a proper literature review and clearly discuss the novelty in the scientific discoveries made in their paper. Technical Novelty: Papers reviewed with this sub-criterion should include novelty in their computational approach for recognizing, generating or modeling data. Examples include: novelty in the learning and prediction algorithms, in the neural architecture, or in the data representation. Novelty can also be associated to a new usage of an existing approach. Please see the Submission Guidelines for Authors for detailed submission instructions. This year, ICMI welcomes contributions on our theme of multi-modal understanding of multi-party interactions. Additional topics of interest include but are not limited to: Affective computing and interaction Cognitive modeling and multimodal interaction Gesture, touch and haptics Healthcare, assistive technologies Human communication dynamics Human-robot/agent multimodal interaction Interaction with smart environment Machine learning for multimodal interaction Mobile multimodal systems Multimodal behavior generation Multimodal datasets and validation Multimodal dialogue modeling Multimodal fusion and representation Multimodal interactive applications Speech behaviors in social interaction System components and multimodal platforms Visual behaviors in social interaction Virtual/augmented reality and multimodal interaction Important Dates Abstract Submission (must include title, authors, abstract) May 1, 2019 (11:59pm PST) Final Submission (final submissions -- no updates allowed after May 7) May 7, 2019 (11:59pm PST) Rebuttal due June 25, 2019 (11:59pm PST) Paper notification July 7, 2019 Paper camera-ready July 15, 2019 (11:59pm PST) Presenting at main conference October 14-18, 2019 Best regards, Social Media Chair ICMI 2019 Zakia Hammal, PhD The Robotics Institute, Carnegie Mellon University http://www.ri.cmu.edu/ http://ri.cmu.edu/personal-pages/ZakiaHammal/

5 years, 11 months

ICMI 2019: Call for Multimodal Grand Challenges

by zakia hammal

Apologies for cross-posting *********************************************************************************** ICMI 2019: Call for Multimodal Grand Challenges https://icmi.acm.org/2019/index.php?id=cfc Submission Deadline: January 14, 2019 *********************************************************************************** Call for Multimodal Grand Challenges Proposals due January 14, 2019 Proposal notification February 1, 2019 Paper camera-ready August 12, 2019 We are calling for teams to propose one or more ICMI Multimodal Grand Challenges. The International Conference on Multimodal Interaction (ICMI) is the premier international forum for multidisciplinary research on multimodal human-human and human-computer interaction, interfaces, and system development. Developing systems that can robustly understand human-human communication or respond to human input requires identifying the best algorithms and their failure modes. In fields such as computer vision, speech recognition, computational (para-) linguistics and physiological signal processing, for example, the availability of datasets and common tasks have led to great progress. We invite the ICMI community to collectively define and tackle the scientific Grand Challenges in our domain for the next 5 years. ICMI Multimodal Grand Challenges aim to inspire new ideas in the ICMI community and create momentum for future collaborative work. Analysis, synthesis, and interactive tasks are all possible. Challenge papers will be indexed in the proceedings of ICMI. The grand challenge sessions are still to be confirmed. We invite organizers from various fields related to multimodal interaction to propose and run Grand Challenge events. We are looking for exciting and stimulating challenges including but not limited to the following categories: Dataset-driven challenge. This challenge will provide a dataset that is exemplary of the complexities of current and future multimodal problems, and one or more multimodal tasks whose performance can be objectively measured and compared in rigorous conditions. Participants in the Challenge will evaluate their methods against the challenge data in order to identify areas of strengths and weakness. Use-case challenge. This challenge will provide an interactive problem system (e.g. dialog-based or non-verbal-based) and the associated resources, which can allow people to participate through the integration of specific modules or alternative full systems. Proposers should also establish systematic evaluation procedures. Health challenge. This challenge will provide a dataset that is exemplary of a health related task, whose analysis, diagnosis, treatment or prevention can be aided by Multimodal Interactions. The challenge should focus on exploring the benefits of multimodal (audio, visual, physiological, etc) solutions for the stated task. Policy challenge. Legal, ethical, and privacy issues of Multimodal Interaction systems in the age of AI. The challenge could revolve around opinion papers, panels, discussions, etc. Prospective organizers should submit a five-page maximum proposal containing the following information: Title Abstract appropriate for possible Web promotion of the Challenge Distinctive topics to be addressed and specific goals Detailed description of the Challenge and its relevance to multimodal interaction Length (full day or half day) Plan for soliciting participation Description of how submissions (challenge’s submissions and papers) will be evaluated, and a list of proposed reviewers Proposed schedule for releasing datasets (if applicable) and/or systems (if applicable) and receiving submissions Short biography of the organizers (preferably from multiple institutions) Funding source (if any) that supports or could support the challenge organization Draft call for papers; affiliations and email address of the organisers; summary of the Grand Challenge; list of potential Technical Program Committee members and their affiliations, important dates Proposals will be evaluated based on originality, ambition, feasibility, and implementation plan. A Challenge with dataset(s) or system(s) that has had pilot results to ensure its representativity and suitability to the proposed task will be given preference for acceptance; an additional 1 page description must be attached in such case. Continuation of or variants on the 2018 challenges are welcome, though we ask for submissions of this form to highlight the number of participants that attended during the previous year and describe what changes will be made from the previous year. The ICMI organizers will offer support with basic logistics, which includes rooms and equipment to run the Workshop, coffee breaks can be offered if synchronised with the main conference. Important Dates and Contact Details Proposals should be emailed to both ICMI 2019 Multimodal Grand Challenge Chairs, Prof Anna Esposito and Dr. Michel Valstar via grandchallenge.ICMI19(a)gmail.com. Prospective organizers are also encouraged to contact the co-chairs if they have any questions. Proposals are due by January 14th, 2019. Notifications will be sent on February 1st, 2019. Best regards, Social Media Chair ICMI 2019 Zakia Hammal, PhD The Robotics Institute, Carnegie Mellon University http://www.ri.cmu.edu/ http://ri.cmu.edu/personal-pages/ZakiaHammal/

5 years, 11 months

ICMI 2019: Call for Workshops

by zakia hammal

Apologies for cross-posting *********************************************************************************** ICMI 2019: Call for Workshops https://icmi.acm.org/2019/index.php?id=CfW Submission Deadline: Saturday, February 16, 2019 *********************************************************************************** Call for Workshops The International Conference on Multimodal Interaction (ICMI 2019) will be held in Suzhou, Jiangsu, China, during October 14-18, 2019. ICMI is the premier international conference for multidisciplinary research on multimodal human-human and human-computer interaction analysis, interface design, and system development. The theme of the ICMI 2019 conference is Multi-modal Understanding of Multi-party Interactions. ICMI has developed a tradition of hosting workshops in conjunction with the main conference to foster discourse on new research, technologies, social science models and applications. Examples of recent workshops include: Multi-sensorial Approaches to Human-Food Interaction Group Interaction Frontiers in Technology Modeling Cognitive Processes from Multimodal Data Human-Habitat for Health Multimodal Analyses enabling Artificial Agents in Human-Machine Interaction Investigating Social Interactions with Artificial Agents Child Computer Interaction Multimodal Interaction for Education We are seeking workshop proposals on emerging research areas related to the main conference topics, and those that focus on multi-disciplinary research. We would also strongly encourage workshops that will include a diverse set of keynote speakers (factors to consider include: gender, ethnic background, institutions, years of experience, geography, etc.). The format, style, and content of accepted workshops are under the control of the workshop organizers. Workshops may be of a half-day or one day in duration. Workshop organizers will be expected to manage the workshop content, be present to moderate the discussion and panels, invite experts in the domain, and maintain a website for the workshop. Workshop papers will be indexed by ACM. Submission Prospective workshop organizers are invited to submit proposals in PDF format (Max. 3 pages). Please email proposals to the workshop chairs: Hongwei Ding (hwding(a)sjtu.edu.cn), Carlos Busso (busso(a)utdallas.edu) and Tadas Baltrusaitis (tadyla(a)gmail.com). The proposal should include the following: Workshop title List of organizers including affiliation, email address, and short biographies Workshop motivation, expected outcomes and impact Tentative list of keynote speakers Workshop format (by invitation only, call for papers, etc.), anticipated number of talks/posters, workshop duration (half-day or full-day) including tentative program Planned advertisement means, website hosting, and estimated participation Paper review procedure (single/double-blind, internal/external, solicited/invited-only, pool of reviewers, etc.) Paper submission and acceptance deadlines Special space and equipment requests, if any Important Dates: Workshop proposal submission: Saturday, February 16, 2019 Notification of acceptance: Saturday, March 2, 2019 Workshop Date: Monday, October 14, 2019 Best regards, Social Media Chair ICMI 2019 Zakia Hammal, PhD The Robotics Institute, Carnegie Mellon University http://www.ri.cmu.edu/ http://ri.cmu.edu/personal-pages/ZakiaHammal/

5 years, 11 months

Call For Chapters | Neural and Machine Learning for Emotion and Empathy Recognition: Experiences from the OMG-Challenges by Springer

by Pablo Barros

Dear Colleagues, We would like to invite you to contribute a chapter for the upcoming volume entitled “Neural and Machine Learning for Emotion and Empathy Recognition: Experiences from the OMG-Challenges” to be published by the Springer Series on Competitions in Machine Learning. Our book will be available by fall 2019. Website: https://easychair.org/cfp/OMGBook2019 Short description of the volume: Emotional expression perception and categorization are extremely popular in the affective computing community. However, the inclusion of emotions in the decision-making process of an agent is not considered in most of the research in this field. To treat emotion expressions as the final goal, although necessary, reduces the usability of such solutions in more complex scenarios. To create a general affective model to be used as a modulator for learning different cognitive tasks, such as modeling intrinsic motivation, creativity, dialog processing, grounded learning, and human-level communication, instantaneous emotion perception cannot be the pivotal focus. This book aims to present recent contributions for multimodal emotion recognition and empathy prediction which take into consideration the long-term development of affective concepts. On this regard, we provide access to two datasets: the OMG-Emotion Behavior Recognition and OMG-Empathy Prediction datasets. These datasets were designed, collected and formalized to be used on the OMG-Emotion Recognition Challenge and the OMG-Empathy Prediction challenge, respectively. All the participants of our challenges are invited to submit their contribution to our book. We also invite interested authors to use our datasets on the development of inspiring and innovative research on affective computing. By formatting these solutions and editing this book, we hope to inspire further research in affective and cognitive computing over longer timescales. TOPICS OF INTEREST The topics of interest for this call for chapters include, but are not limited to: - New theories and findings on continuous emotion recognition - Multi- and Cross-modal emotion perception and interpretation - Novel neural network models for affective processing - Lifelong affect analysis, perception, and interpretation - New neuroscientific and psychological findings on continuous emotion representation - Embodied artificial agents for empathy and emotion appraisal - Machine learning for affect-driven interventions - Socially intelligent human-robot interaction - Personalized systems for human affect recognition - New theories and findings on empathy modeling - Multimodal processing of empathetic and social signals - Novel neural network models for empathy understanding - Lifelong models for empathetic interactions - Empathetic Human-Robot-Interaction Scenarios - New neuroscientific and psychological findings on empathy representation - Multi-agent communication for empathetic interactions - Empathy as a decision-making modulator - Personalized systems for empathy prediction Each contributed chapter is expected to present a novel research study, a comparative study, or a survey of the literature. We also expect that each contributed chapter approach somehow at least one of our datasets: the OMG-Emotion and the OMG-Empathy. SUBMISSIONS All submissions should be done via EasyChair: https://easychair.org/cfp/OMGBook2019 Original artwork and a signed copyright release form will be required for all accepted chapters. For author instructions, please visit: https://www.springer.com/us/authors-editors/book-authors-editors/resources-… ACCESS TO THE DATASETS - OMG-EMOTION - https://www2.informatik.uni-hamburg.de/wtm/omgchallenges/omg_emotion.html - OMG-EMPATHY - https://www2.informatik.uni-hamburg.de/wtm/omgchallenges/omg_empathy.html To have access to the datasets, please send an e-mail to: barros(a)informatik.uni-hamburg.de IMPORTANT DATES: - Submission of abstracts: 08th of February 2019 - Notification of initial editorial decisions: 15th of February 2019 - Submissions of full-length chapters: 29th of March 2019 - Notification of final editorial decisions 17th of May 2019 - Submission of revised chapters: 07th of June, 2019 -- Best regards, *Pablo Barros* *http://www.pablobarros.net <http://www.pablobarros.net>*

5 years, 12 months

CFP: TAC | Special Issue on Automated Perception of Human Affect from Longitudinal Behavioral Data

by Pablo Barros

2nd CALL FOR PAPERS IEEE Transactions on Affective Computing Special Issue on Automated Perception of Human Affect from Longitudinal Behavioral Data Website: https://www2.informatik.uni-hamburg.de/wtm/omgchallenges/tacSpecialIssue201… I. Aim and Scope Research trends within artificial intelligence and cognitive sciences are still heavily based on computational models that attempt to imitate human perception in various behavior categorization tasks. However, most of the research in the field focuses on instantaneous categorization and interpretation of human affect, such as the inference of six basic emotions from face images, and/or affective dimensions (valence-arousal), stress and engagement from multi-modal (e.g., video, audio, and autonomic physiology) data. This diverges from the developmental aspect of emotional behavior perception and learning, where human behavior and expressions of affect evolve and change over time. Moreover, these changes are present not only in the temporal domain but also within different populations and more importantly, within each individual. This calls for a new perspective when designing computational models for analysis and interpretation of human affective behaviors: the computational models that can timely and efficiently adapt to different contexts and individuals over time, and also incorporate existing neurophysiological and psychological findings (prior knowledge). Thus, the long-term goal is to create life-long personalized learning and inference systems for analysis and perception of human affective behaviors. Such systems would benefit from long-term contextual information (including demographic and social aspects) as well as individual characteristics. This, in turn, would allow building intelligent agents (such as mobile and robot technologies) capable of adapting their behavior in a continuous and on-line manner to the target contexts and individuals. This special issue aims at contributions from computational neuroscience and psychology, artificial intelligence, machine learning, and affective computing, challenging and expanding current research on interpretation and estimation of human affective behavior from longitudinal behavioral data, i.e., single or multiple modalities captured over extended periods of time allowing efficient profiling of target behaviors and their inference in terms of affect and other socio-cognitive dimensions. We invite contributions focusing on both the theoretical and modeling perspective, as well as applications ranging from human-human, human-computer and human-robot interactions. II. Potential Topics Given computational models, the capability to perceive and understand emotion behavior is an important and popular research topic. That is why recent special issues on the IEEE Journal on Transactions on Affective Computing covered topics from emotion behavior analysis “in-the-wild” to personality analysis. However, most of the research published by these specific calls treat emotion behavior as an instantaneous event, relating mostly to emotion recognition, and thus neglect the development of complex emotion behavior models. Our special issue will foster the development of the field by focusing excellent research on emotion models for long-term behavior analysis. The topics of interest for this special issue include, but are not limited to: - New theories and findings on continuous emotion recognition - Multi- and Cross-modal emotion perception and interpretation - Lifelong affect analysis, perception, and interpretation - Novel neural network models for affective processing - New neuroscientific and psychological findings on continuous emotion representation - Embodied artificial agents for empathy and emotion appraisal - Machine learning for affect-driven interventions - Socially intelligent human-robot interaction - Personalized systems for human affect recognition III. Submission Prospective authors are invited to submit their manuscripts electronically, adhering to the IEEE Transactions on Affective Computing guidelines ( https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=5165369). Please submit your papers through the online system ( https://mc.manuscriptcentral.com/taffc-cs) and be sure to select the special issue: Special Issue/Section on Automated Perception of Human Affect from Longitudinal Behavioral Data. IV. IMPORTANT DATES: Submissions Deadline: 15th of January 2019 Deadline for reviews and response to authors: 06th of April 2019 Camera-ready deadline: 05th of August 2019 V. Guest Editors Pablo Barros, University of Hamburg, Germany Stefan Wermter, University of Hamburg, Germany Ognjen (Oggi) Rudovic, Massachusetts Institute of Technology, United States of America Hatice Gunes, University of Cambridge, United Kingdom -- Dr. Pablo Barros Postdoctoral Research Associate - Crossmodal Learning Project (CML) Knowledge Technology Department of Informatics University of Hamburg Vogt-Koelln-Str. 30 22527 Hamburg, Germany Phone: +49 40 42883 2535 Fax: +49 40 42883 2515 barros at informatik.uni-hamburg.dehttp://www.pablobarros.nethttps://www.inf.uni-hamburg.de/en/inst/ab/wtm/people/barros.htmlhttps://www.inf.uni-hamburg.de/en/inst/ab/wtm/

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Face-research-list