Face-research-list January 2019

face-research-list@lists.stir.ac.uk

7 participants
13 discussions

Expressions of Interest for Future Research Leaders Fellowship @ University of Glasgow

by Rachael Jack

Dear colleagues, I would be grateful if you could share this call for EoIs with your colleagues and on your mailing lists. Deadline 4 FEB 2019. Thanks The Center for Social, Cognitive, Affective Neuroscience (cSCAN<http://cscan.gla.ac.uk/>: <<http://cscan.gla.ac.uk/>http://cscan.gla.ac.<http://cscan.gla.ac.uk/>uk>),<http://cscan.gla.ac.uk/> <http://cscan.gla.ac.uk/> at the University of Glasgow, Scotland seeks expressions of interest (EoI) in the Future Leaders Fellowship (FLF) from UK Research and Innovation <www.ukri.org/funding/funding-opportunities/future-leaders-fellowships/<http://www.ukri.org/funding/funding-opportunities/future-leaders-fellowship…>>. The FLF seeks to “develop, retain, attract and sustain research and innovation talent in the UK” and offers a research-focused post for 4 years, plus a possible 3 additional years, followed by an ongoing academic post within cSCAN. cSCAN researchers address fundamental mechanisms of social perception, social cognition, and social interaction from a unique, highly transdisciplinary perspective that spans psychology, neuroscience and the computational/engineering sciences. More details can be found at <cscan<http://cscan.gla.ac.uk/>.gla.ac.<http://cscan.gla.ac.uk/>uk<http://cscan.gla.ac.uk/>>. Only candidates who are early-career researchers (within ~6-7 years post-PhD) with very strong publication records relative to career stage and with clear value-added to the cSCAN research program will be considered. Please email rachael.jack(a)glasgow.ac.uk<mailto:rachael.jack@glasgow.ac.uk> a current CV and a 2-page research statement by Feb 4th, 2019 at the latest. Include ‘Interest in Future Leaders Fellowship’ in the subject of the email. We will be in touch with applicants who are short-listed to progress to the next stage and work with them to develop applications to submit to UKRI. Applicants should refer to the UKRI website for deadline information. Dr. Rachael E. Jack, Ph.D. Reader Institute of Neuroscience & Psychology School of Psychology University of Glasgow +44 (0) 141 5087 www.psy.gla.ac.uk/schools/psychology/staff/rachaeljack/

6 years, 1 month

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 *********************************************************************************** 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/

6 years, 1 month

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

by zakia hammal

6 years, 1 month

Complex emotional face stimuli

by Nicola Jones

Dear all, I am on the hunt for a face database that contains expressions of embarrassment, guilt, flirtation, boredom, arrogance and admiration, as well as neutral and basic emotions (e.g. neutral, happy, angry, sad etc.) for an EEG experiment I am running with a dissertation student of mine. If anyone can point me in the right direction or has access to a number of faces with these expressions, I would be most grateful! Best wishes, Nicola --

6 years, 1 month

different average faces

by Rachel Robbins

Dear face researchers, We want to create caricatures for some famous faces that we used in an experiment last year. These include both men and women and a range of ages from mid-20s to 60-70s (and the queen). All are Caucasian/White. Does anyone have average faces for male and female for approx <30 years, 30-60 years and 60+ years, that they would be willing to share with us? We also have the problem that many but not all the faces are showing teeth, so we will probably need different averages for the mouth with teeth showing versus no teeth showing versions... Thanks! Rachel -- “It is not our differences that divide us. It is our inability to recognize, accept, and celebrate those differences.” - Audre Lorde

6 years, 1 month

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/

6 years, 1 month

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.*

6 years, 1 month

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/

6 years, 2 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/

6 years, 2 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>*

6 years, 2 months

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Face-research-list January 2019