Face-research-list

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Call for abstracts: 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

Dear colleagues, We are inviting abstract 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 follow below. Title, abstract, list of authors, as well as the name of the corresponding author, should be emailed directly to Abhijit Das (abhijitdas2048(a)gmail.com). We hope to receive abstracts before Thursday, September 27th. 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) -------------------------------------------------------------------------------------------- *Call for abstract for FG 2018 special session * *on* *Human Health Monitoring Based on Computer Vision* --------------------------------------------------------------- Human Health Monitoring Based on Computer Vision has gained rapid scientific growth in the last years, with many research articles and complete systems based on a set of features, extracted from face and gesture. Researchers from the computer, as well as from medical science have granted significant attention, with goals ranging from patient analysis and monitoring to diagnostics. (e.g., for dementia, depression, healthcare, physiological measurement [5, 6]). Despite the progress, there are various open, unexplored, and unidentified challenges. Such as the robustness of these techniques in the real-world scenario, collecting large dataset for research, heterogeneity of the acquiring environment and the artefacts. Moreover, healthcare represents an area of broad economic (e.g., https://www.prnewswire.com/news-releases/healthcare-automation-market-to-re…), social, and scientific impact. Therefore, it is imperative to foster efforts coming from computer vision, machine learning, and the medical domain, as well as multidisciplinary efforts. Towards this, we propose a special session, with a focus on multidisciplinary efforts. We aim to document recent advancements in automated healthcare, as well as enable and discuss progress.. Therefore, the goal of this special session is to bring together researchers and practitioners working in this area of computer vision and medical science, and to address a wide range of theoretical and practical issues related to real-life healthcare systems. Topics of interest include, but are not limited to: · Health monitoring based on face analysis, · Health monitoring based on gesture analysis, · Health monitoring based corporeal-based visual features, · Depression analysis based on visual features, · Face analytics for human behaviour understanding, · Anxiety diagnosis based on face and gesture · Physiological measurement employing face analytics, · Databases on health monitoring, e.g., depression analysis, · Augmentative and alternative communication, · Human-robot interaction, · Home healthcare, · Technology for cognition, · Automatic emotional hearing and understanding, · Visual attention and visual saliency, · Assistive living, · Privacy preserving systems, · Quality of life technologies, · Mobile and wearable systems, · Applications for the visually impaired, · Sign language recognition and applications for hearing impaired, · Applications for the ageing society, · Personalized monitoring, · Egocentric and first-person vision, · Applications to improve the health and wellbeing of children and the elderly, etc. In addition, we plan to organise a special issue in a journal with the extended version of accepted special session papers.

6 years, 10 months

Resources for Gestures and Emotion Recognition

by Pablo Barros

Dear all, We are very happy to announce the release of resource material related to our research on affective computing and gestures recognition. This resource contains research on hand gesture and emotion processing (auditory, visual and crossmodal) recognition and processing, organized as three datasets (NCD, GRIT, and OMG-Emotion), source code for proposed neural network solutions, pre-trained models, and ready-to-run demos. The NAO Camera hand posture Database (NCD) was designed and recorded using the camera of a NAO robot and contains four different hand postures. A total of 2000 images were recorded. In each image, the hand was is present in different positions, not always in the centralized, and sometimes with occlusion of some fingers. The Gesture Commands for Robot InTeraction (GRIT) dataset contains recordings of six different subjects performing eight command gestures for Human-Robot Interaction (HRI): Abort, Circle, Hello, No, Stop, Turn Right, Turn Left, and Warn. We recorded a total of 543 sequences with a varying number of frames in each one. The One-Minute Gradual Emotion Corpus (OMG-Emotion) is composed of Youtube videos which are about a minute in length and are annotated taking into consideration a continuous emotional behavior. The videos were selected using a crawler technique that uses specific keywords based on long-term emotional behaviors such as "monologues", "auditions", "dialogues" and "emotional scenes". After the videos were selected, we created an algorithm to identify weather the video had at least two different modalities which contribute for the emotional categorization: facial expressions, language context, and a reasonably noiseless environment. We selected a total of 420 videos, totaling around 10 hours of data. Together with the datasets, we provide the source code for different proposed neural models. These models are based on novel deep and self-organizing neural networks which deploy different mechanisms inspired by neuropsychological concepts. All of our models are formally described in different high-impact peer-reviewed publications. We also provide a ready-to-run demo for visual emotion recognition based on our proposed models. These resources are accessible through our GitHub link: https://github.com/knowledgetechnologyuhh/EmotionRecognitionBarros . We hope that with these resources we can contribute to the areas of affective computing and gesture recognition and foster the development of innovative solutions. -- Dr.rer.nat. 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.de https://www.inf.uni-hamburg.de/en/inst/ab/wtm/people/barros.html https://www.inf.uni-hamburg.de/en/inst/ab/wtm/

6 years, 11 months

Open Positions: 1 Ph.D. student and 2 Postdocs in the area of Computer Vision and Deep Learning at INRIA Sophia Antipolis, France

by Antitza Dantcheva

Open Positions: 1 Ph.D. student and 2 Postdocs in the area of Computer Vision and Deep Learning at INRIA Sophia Antipolis, France ------------------------------ ------------------------------ ------------------------------ ------------------------------ ------------------------------ ---------------------- Positions are offered within the frameworks of the prestigious grants - ANR JCJC Grant *ENVISION*: "Computer Vision for Automated Holistic Analysis for Humans" and the - INRIA - CAS grant *FER4HM* "Facial expression recognition with application in health monitoring" and are ideally located in the heart of the French Riviera, inside the multi-cultural silicon valley of Europe. Full announcements: - Open Ph.D.-Position in Computer Vision / Deep Learning (M/F) *ENVISION*: http://antitza.com/ANR_phd.pdf - Open Post Doc - Position in Computer Vision / Deep Learning (M/F) *FER4HM*: http://antitza.com/INRIA_CAS_p ostdoc.pdf - Open Post Doc - Position in Computer Vision / Deep Learning (M/F) (advanced level) *ENVISION*: http://antitza.com/ANR_postdoc .pdf To apply, please email a full application to Antitza Dantcheva ( antitza.dantcheva(a)inria.fr ), indicating the position in the e-mail subject line.

6 years, 11 months

Mooney face data base online

by Caspar M. Schwiedrzik

Dear all, we just published a database of 500 Mooney face stimuli for visual perception research. Please find the paper here: http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0200106 Each face was tested in a cohort of healthy adults for face detection difficulty and inversion effects. We also provide a comparison with Craig Mooney's original stimulus set. The stimuli and accompanying data are available from Figshare (https://figshare.com/account/articles/5783037) under a CC BY license. Please feel free to use them for your research. Caspar

7 years

Lab Manager/Research Assistant position available at the University of Richmond

by BURNS E. (597993)

RESEARCH SPECIALIST POSITION AT COGNITIVE NEUROSCIENCE LAB, University of Richmond The Cognitive Neuroscience laboratory of Dr. Cindy Bukach is seeking a highly organized and energetic person to serve as full-time research specialist. The lab conducts research on object and face recognition in cognitively intact and impaired individuals, using electrophysiology (EEG and ERP) and behavioral methods. The duties of the research specialist include: Conducts Cognitive Neuroscience research on human subjects using both behavioral and ERP methods, including programming, recruiting, testing and statistical analysis. Under limited supervision, coordinates and supervises student research activities, ensuring adherence to safety and ethical regulations related to research with human subjects. Performs administrative duties such as database management, scheduling, hardware/software maintenance, website maintenance, equipment maintenance and general faculty support. EDUCATION & EXPERIENCE: Bachelor’s degree or equivalent in psychology, neuroscience, cognitive science, computer science or related field 2 years experience in a research lab (preferably in cognitive or cognitive neuroscience laboratory using Event-related potential method) PREFERRED QUALIFICATIONS (any of the following highly desired): Prior research experience with Event-related potential method and data analysis Advanced computer skills (Matlab, Python, Java, etc.) For more information, please contact Cindy Bukach at cbukach(a)richmond.edu<mailto:cbukach@richmond.edu> Cindy M. Bukach, PhD Chair, Department of Psychology Associate Professor of Cognitive Neuroscience MacEldin Trawick Endowed Professor of Psychology 209 Richmond Hall 28 Westhampton Way University of Richmond, Virginia 23173 Phone: (804) 287-6830 Fax: (804) 287-1905

7 years, 1 month

PhD scholarship in face identification at UNSW Sydney

by David White

Call for Expressions of Interest: UNSW Scientia PhD Scholarship "Understanding super-recognition to improve face identification systems" The UNSW Forensic Psychology Group invites Expressions of Interest for a unique PhD scholarship opportunity. UNSW Scientia PhD scholars are awarded $50k per year, comprising a tax-free living allowance of $40k per year for 4 years, and a support package of up to $10k per year to provide financial support for career development activities. The project is targeted at PhD candidates that are qualified to honours and/or masters level in psychology, computer science of cognitive science. We are particularly interested to hear from applicants with work experience in research, government or industry. The topic of this thesis is open to negotiation, but we hope that the work can contribute to our broader goal of understanding how the best available human and machine solutions to face identification can be combined to produce optimal systems. For more details and to apply see the following links: https://www.2025.unsw.edu.au/apply/scientia-phd-scholarships/understanding-… http://forensic.psy.unsw.edu.au/joinus.html https://www.2025.unsw.edu.au/apply/<https://www.2025.unsw.edu.au/apply/scientia-phd-scholarships/understanding-…> Please direct informal inquiries to david.white(a)unsw.edu.au<mailto:david.white@unsw.edu.au>

7 years, 1 month

Postdoc positions @ U Glasgow

by Rachael Jack

Dear colleagues – please circulate widely! We are delighted to announce the following positions at the Institute of Neuroscience & Psychology, University of Glasgow, Scotland. All positions are funded by the ERC project Computing the Face Syntax of Social Communication led by Dr. Rachael Jack. 2 X Postdoctoral Researcher (5 years) Ref: 021275 The post-holders will contribute to a large 5-year research project to model culture-specific dynamic social face signals with transference to social robotics. The post requires expert knowledge in all or a substantial subset of the following: vision science, psychophysics, social perception, cultural psychology, dynamic social face signalling, human-robot interaction, reverse correlation techniques, MATLAB programming, computational methods, and designing behavioral experiments. Informal enquiries may be made to Dr Rachael Jack Email: Rachael.Jack(a)glasgow.ac.uk<mailto:Rachael.Jack@glasgow.ac.uk> Apply online at: www.glasgow.ac.uk/jobs<http://www.glasgow.ac.uk/jobs> Closing date: 12 June 2018<x-apple-data-detectors://2> See also http://www.jobs.ac.uk/job/BJU668/research-assistant-associate/ The University has recently been awarded the Athena SWAN Institutional Bronze Award. The University is committed to equality of opportunity in employment. The University of Glasgow, charity number SC004401. Dr. Rachael E. Jack, Ph.D. Lecturer Institute of Neuroscience & Psychology School of Psychology University of Glasgow +44 (0) 141 5087<tel:+44%20141%205087> www.psy.gla.ac.uk/schools/psychology/staff/rachaeljack/<http://www.psy.gla.ac.uk/schools/psychology/staff/rachaeljack/> [University of Glasgow: The Times Scottish University of the Year 2018]

7 years, 2 months

OMG- Emotion Recognition Challenge - Final Results

by Pablo Barros

Dear all, I would like to share with you all the results of our first OMG- Emotion Recognition Challenge. Our challenge is based on the One-Minute-Gradual Emotion Dataset (OMG-Emotion Dataset), which is composed of 567 emotion videos with an average length of 1 minute, collected from a variety of Youtube channels. Each team had a task to describe each video with a continuous space of arousal/valence domain. The challenge had a total of 34 teams registered, from which we got 11 final submissions. Each final submission was composed of a short paper describing the solution and the link to the code repository. The solutions used different modalities (ranging from unimodal audio and vision to multimodal audio, vision, and text), and thus provide us with a very complex evaluation scenario. All the submissions were based on neural network models. We split results into arousal and valence. For arousal, the best results came from the GammaLab team. Their three submissions are our top 3 CCC arousal, followed by the three submissions from the audEERING team, and the two submissions from the HKUST-NISL2018 team. For valence, the GammaLab team stays still in first (with their three submissions), followed by the two submissions of ADSC team and the three submissions from the iBug team. Congratulations to you all! We provide a leaderboard on our website ( https://www2.informatik.uni-hamburg.de/wtm/OMG-EmotionChallenge/ ), which will be permanently stored. This way, everyone can see the final results of the challenge, have a quick access to a formal description of the solutions and to the codes. This will help to disseminate knowledge even further and will improve the reproducibility of your solutions. We also provide a general leaderboard which will be updated constantly with new submissions. If you are interested in having your score in our general leaderboard, just send us an e-mail following the instructions on our website. I would also to invite you all to the presentation of the challenge summary during the WCCI/IJCNN 2018 in Rio de Janeiro, Brasil. Best Regards, Pablo -- 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.de https://www.inf.uni-hamburg.de/en/inst/ab/wtm/people/barros.html https://www.inf.uni-hamburg.de/en/inst/ab/wtm/

7 years, 2 months

Research Associate

by Psychology-Admin

Please see attached an advert for a Research Associate position working with Dr Rachael Jack within the School of Psychology/Institute of Neuroscience & Psychology. Informal enquiries can be directed to Rachael Email: Rachael.Jack(a)glasgow.ac.uk<mailto:Rachael.Jack@glasgow.ac.uk> [University of Glasgow: The Times Scottish University of the Year 2018]

7 years, 2 months

Face and gesture recognition meeting

by Peter Hancock

This year's automatic face and gesture recognition conference has not yet happened but we already have the call for next year's which will be in France. There is a desire to get more cross-fertilisation between psychology and computer science in this field; I think it would be great to have a session on the latest advances in understanding the psychology of face perception. Please think whether you might have something useful to say. Thanks, Peter Peter Hancock Professor, Deputy Head of Psychology, Faculty of Natural Sciences University of Stirling FK9 4LA, UK phone 01786 467675 fax 01786 467641 http://stir.ac.uk/190 http://orcid.org/0000-0001-6025-7068 http://www.researcherid.com/rid/A-4633-2009 Psychology at Stirling: 100% 4* Impact, REF2014 Come and study Face Perception at the University of Stirling! Our unique MSc in the Psychology of Faces is open for applications. For more information see http://www.stir.ac.uk/postgraduate/programme-information/prospectus/psychol… [highly cited 2016]

7 years, 2 months

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