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CFP: TAC | Special Issue on Automated Perception of Human Affect from Longitudinal Behavioral Data
by Pablo Barros 07 Jan '19

07 Jan '19

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>*

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ICMI 2019: Call for Long and Short Papers
by zakia hammal 03 Jan '19

03 Jan '19

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/

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ICMI 2019: Call for Multimodal Grand Challenges
by zakia hammal 03 Jan '19

03 Jan '19

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/

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ICMI 2019: Call for Workshops
by zakia hammal 03 Jan '19

03 Jan '19

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/

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Call For Chapters | Neural and Machine Learning for Emotion and Empathy Recognition: Experiences from the OMG-Challenges by Springer
by Pablo Barros 27 Dec '18

27 Dec '18

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>*

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CFP: TAC | Special Issue on Automated Perception of Human Affect from Longitudinal Behavioral Data
by Pablo Barros 11 Dec '18

11 Dec '18

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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Call For Participation in Sclera Segmentation Benchmarking Competition (SSBC 2019) in conjunction with ICB 2019
by Abhijit Das 22 Nov '18

22 Nov '18

Dear colleagues, We are inviting participation to biometric competition on "6th *Sclera Segmentation Recognition Benchmarking Competition(SSBC 2019)", *in conjunction with the 12th* IAPR **International Conference on Biometrics (ICB 2019)*. Details about the competition can be found at https://sites.google.com/view/ssbc2019/home Please find a call for participation flyer attached with the email. Please feel free to register for the same. *We will** welcome the top ranking participant to join as co-author of the technical report of the competition that will be submitted to ICB 2019**.* Feel free to contact Abhijit Das if you have any further questions. Kindly circulate this email to others who might be interested. We look forward to your contributions! Best regards Organizers SSBC 2019 Abhijit Das (Inria, France) Umpada Pal (ISI, Kolkata, India) Michael Blumenstein (UTS , Australia)

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Call for paper: special session on human health monitoring based on computer vision, IEEE International Conference on Automatic Face and Gesture Recognition (FG’19), Lille, France, May 14-18, 2019.
by Abhijit Das 22 Nov '18

22 Nov '18

Dear colleagues, We are inviting paper submissions for a special session on “Human Health Monitoring Based on Computer Vision”, as part of the 14th IEEE International Conference on Automatic Face and Gesture Recognition (FG’19, http://fg2019.org/) Lille, France, May 14-18, 2019. Details on the special session can be found in the attached call for paper and at http://fg2019.org/participate/special-sessions/hhmbcv/. IMPORTANT DATES: Full Paper Submission: Dec 14th, 2018 Acceptance Notification: Jan 21st, 2019 Camera-Ready Paper Due: Feb 15th 2019 Feel free to contact Abhijit Das if you have any further questions. Kindly circulate this email to others who might be interested. We look forward to your contributions! François Brémond (INRIA, France) Antitza Dantcheva (INRIA, France) Abhijit Das (INRIA, France) Xilin Chen (CAS, China) Hu Han (CAS, China)

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2nd CFP: The OMG-Empathy Prediction Challenge
by Pablo Barros 14 Nov '18

14 Nov '18

2nd CALL FOR PARTICIPATION The One-Minute Gradual-Empathy Prediction (OMG-Empathy) Competition held in partnership with the IEEE International Conference on Automatic Face and Gesture Recognition 2019 in Lille, France. https://www2.informatik.uni-hamburg.de/wtm/omgchallenges/omg_empathy.html I. Aim and Scope The ability to perceive, understand and respond to social interactions in a human-like manner is one of the most desired capabilities in artificial agents, particularly social robots. These skills are highly complex and require a focus on several different aspects of research, including affective understanding. An agent which is able to recognize, understand and, most importantly, adapt to different human affective behaviors can increase its own social capabilities by being able to interact and communicate in a natural way. 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, only emotion perception cannot be the pivotal focus. The integration of perception with intrinsic concepts of emotional understanding, such as a dynamic and evolving mood and affective memory, is required to model the necessary complexity of an interaction and realize adaptability in an agent's social behavior. Such models are most necessary for the development of real-world social systems, which would communicate and interact with humans in a natural way on a day-to-day basis. This could become the next goal for research on Human-Robot Interaction (HRI) and could be an essential part of the next generation of social robots. For this challenge, we designed, collected and annotated a novel corpus based on human-human interaction. This novel corpus builds on top of the experience we gathered while organizing the OMG-Emotion Recognition Challenge, making use of state-of-the-art frameworks for data collection and annotation. The One-Minute Gradual Empathy datasets (OMG-Empathy) contain multi-modal recordings of different individuals discussing predefined topics. One of them, the actor, shares a story about themselves while the other, the listener, reacts to it emotionally. We annotated each interaction based on the listener's own assessment of how they felt while the interaction was taking place. We encourage the participants to propose state-of-the-art solutions not only based on deep, recurrent and self-organizing neural networks but also traditional methods for feature representation and data processing. We also enforce that the use of contextual information, as well as personalized solutions for empathy assessment, will be extremely important for the development of competitive solutions. II. Competition Tracks We let available for the challenge a pre-defined set of training, validation and testing samples. We separate our samples based on each story: 4 stories for training, 1 for validation and 3 for testing. Each story sample is composed of 10 videos with interactions, one for each listener. Although using the same training, validation and testing data split, we propose two tracks which will measure different aspects of self-assessed empathy: The Personalized Empathy track, where each team must predict the empathy of a specific person. We will evaluate the ability of proposed models to learn the empathic behavior of each of the subjects over a newly perceived story. We encourage the teams to develop models which take into consideration the individual behavior of each subject in the training data. The Generalized Empathy track, where the teams must predict the general behavior of all the participants over each story. We will measure the performance of the proposed models to learn a general empathic measure for each of the stories individually. We encourage the proposed models to take into consideration the aggregated behavior of all the participants for each story and to generalize this behavior in a newly perceived story. The training and validation samples will be given to the participants at the beginning of the challenge together with all the associated labels. The test set will be given to the participants without the associated labels. The team`s predictions on the test set will be used to calculate the final metrics of the challenge. III. How to Participate To participate in the challenge, please send us an email to barros @ informatik.uni-hamburg.de with the title "OMG-Empathy Team Registration". This e-mail must contain the following information: Team Name Team Members Affiliation Participating tracks We split the corpus into three subsets: training, validation, and testing. The participants will receive the training and validation sets, together with the associated annotations once they subscribe to the challenge. The subscription will be done via e-mail. Each participating team must consist of 1 to 5 participants and must agree to use the data only for scientific purposes. Each team can choose to take part in one or both the tracks. After the training period is over, the testing set will be released without the associated annotations. Each team must submit, via e-mail, their final predictions as a .csv file for each video on the test set. Together with the final submission, each team must send a short 2-4 pages paper describing their solution published on Arxiv and the link for a GitHub page to their solution. If a team fails to submit any of these items, their submission will be invalidated. Each team can submit 3 complete submissions for each track. IV. Important Dates 25th of September 2018 - Opening of the Challenge - Team registrations begin 1st of October 2018 - Training/validation data and annotation available 3rd of December 2018 - Test data release 5th of December 2018 - Final submission (Results and code) 7th of December 2018 - Final submission (Paper) 10th of December 2018 - Announcement of the winners V. Organization Pablo Barros, University of Hamburg, Germany Nikhil Churamani, University of Cambridge, United Kingdom Angelica Lim, Simon Fraser University, Canada Stefan Wermter, Hamburg University, Germany -- 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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Postdoctoral Fellowship opportunities in Singapore
by Charles Or 09 Nov '18

09 Nov '18

Nanyang Technological University (NTU) in Singapore has open calls for several postdoctoral fellowships, which are also open for research on vision and perception. There are currently three labs in the area of vision research: - Charles OR (charlesor(a)ntu.edu.sg<mailto:charlesor@ntu.edu.sg>) Face perception, motion perception, form perception, EEG, eye movements, computational modelling, psychophysics; http://research.ntu.edu.sg/expertise/academicprofile/Pages/StaffProfile.asp… - Gerrit MAUS (maus(a)ntu.edu.sg<mailto:maus@ntu.edu.sg>) Eye movements, eye blinks, filling-in, interpolation and extrapolation in vision, prediction, motion perception; psychophysics, fMRI, TMS; http://blogs.ntu.edu.sg/perception - Hong XU (xuhong(a)ntu.edu.sg<mailto:xuhong@ntu.edu.sg>) Heading/Self-motion perception in navigation, face and object perception, attention and eye movements, virtual reality, EEG, electrophysiology, modelling, psychophysics; http://www.ntu.edu.sg/home/xuhong/ We have access to state-of-the-art facilities for psychophysics, virtual reality, eye tracking, EEG, MEG, fMRI, fNIRS, TMS, and tDCS. Feel free to contact any of us for more information or to discuss potential proposals. The fellowship ad below (Deadline: 30 November) is currently offered by the College of Humanities, Arts, and Social Sciences, NTU. There are two more opportunities available at NTU: - for research related to Artificial Intelligence (Walllenberg - NTU Presidential Postdoctoral Fellowship, http://www.ntu.edu.sg/ppf/Pages/home.aspx) - for research in any area by PhD graduates from Swedish Universities (Wallenberg - NTU Postdoctoral Fellowship, call open from Dec 1st, https://kaw.wallenberg.org/utlysningar/wallenberg-foundation-postdoctoral-f…) Best Regards, Charles OR, Gerrit MAUS, Hong XU Assistant Professors (Psychology) School of Social Sciences College of Humanities, Arts, and Social Sciences Nanyang Technological University, Singapore ====== The College of Humanities, Arts, and Social Sciences, Nanyang Technological University (NTU) invites applications from eligible candidates to join us as Postdoctoral Fellows for the Academic Year 2019. The Postdoctoral Fellowships are for one year, renewable for a second year, subject to satisfactory performance. Applicants are strongly advised to explore the research interests of the College’s faculty members to identify potential faculty mentors. Applicants must possess a doctoral degree issued no more than 3 years prior to the time of application (i.e. the degree must have been obtained after Jan 1, 2016). Candidates who are finishing up their degrees must have their doctoral degrees conferred by July 2019. Owing to the interdisciplinary nature of the fellowship, applicants are expected to propose a research project to demonstrate how their expertise crosses different disciplines and relates to the specific Research Theme they are applying for. Details are available at: http://class.cohass.ntu.edu.sg/Research/Pages/Postdoctoral-Fellowship-2019.… Applications and Reference Letters must reach the College by 30 November, 2018 (11:59pm Singapore Time UTC+8). Successful candidates are expected to commence their Fellowships in July or August 2019. Owing to the tight deadline, interested candidates are invited to contact potential faculty mentors as soon as possible, with curriculum vitae and a brief research statement provided. Application and enquiries should be addressed to: The Associate Dean (Research) College of Humanities, Arts, and Social Sciences Email: AD-HASS-RESEARCH(a)ntu.edu.sg<mailto:AD-HASS-RESEARCH@ntu.edu.sg> NTU is a young and research-intensive university ranking consistently amongst the top 10 in Asia and the 1st amongst young universities under 50. It has been ranked consistently and progressively under the top 100 universities in the world by the Times Higher Education since 2013, with its latest ranking at 51. Singapore is a fascinating, dynamic multi-cultural city in Southeast Asia with a large expat community, and a great hub for exploring neighbouring travel destinations. ======= ________________________________ CONFIDENTIALITY: This email is intended solely for the person(s) named and may be confidential and/or privileged. If you are not the intended recipient, please delete it, notify us and do not copy, use, or disclose its contents. Towards a sustainable earth: Print only when necessary. Thank you.

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