Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/20503
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dc.contributor.authorEgede, J-
dc.contributor.authorOlugbade, TA-
dc.contributor.authorWang, C-
dc.contributor.authorSong, S-
dc.contributor.authorBerthouze, N-
dc.contributor.authorValstar, MF-
dc.contributor.authorWilliams, ACDC-
dc.contributor.authorMeng, H-
dc.contributor.authorAung, MH-
dc.contributor.authorLane, N-
dc.coverage.spatialBuenos Aires, Argentina-
dc.date.accessioned2020-03-12T13:35:22Z-
dc.date.available2020-03-12T13:35:22Z-
dc.date.issued2020-11-16-
dc.identifierORCiD: Hongying Meng https://orcid.org/0000-0002-8836-1382-
dc.identifier.citationEgede, J. et al. (2020) 'EMOPAIN Challenge 2020: Multimodal Pain Evaluation from Facial and Bodily Expressions, 2020 15th IEEE International Conference on Automatic Face and Gesture Recognition (FG 2020), Buenos Aires, Argentina, 16-20 November, pp. 1 - 8. doi: 10.1109/FG47880.2020.00078.en_US
dc.identifier.isbn978-1-7281-3080-4 (PoD)-
dc.identifier.isbn978-1-7281-3079-8 (ebk)-
dc.identifier.urihttps://bura.brunel.ac.uk/handle/2438/20503-
dc.description.abstractThe EmoPain 2020 Challenge is the first international competition aimed at creating a uniform platform for the comparison of multi-modal machine learning and multimedia processing methods of chronic pain assessment from human expressive behaviour, and also the identification of pain-related behaviours. The objective of the challenge is to promote research in the development of assistive technologies that help improve the quality of life for people with chronic pain via real-time monitoring and feedback to help manage their condition and remain physically active. The challenge also aims to encourage the use of the relatively underutilised, albeit vital bodily expression signals for automatic pain and pain-related emotion recognition. This paper presents a description of the challenge, competition guidelines, bench-marking dataset, and the baseline systems' architecture and performance on the Challenge's three sub-tasks: pain estimation from facial expressions, pain recognition from multimodal movement, and protective movement behaviour detection.en_US
dc.description.sponsorshipEPSRC grant Emotion & Pain Project EP/H017178/1; NIHR Nottingham Biomedical Research Centre.en_US
dc.format.extent1 - 8-
dc.language.isoenen_US
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)en_US
dc.rightsCopyright © 2020 Institute of Electrical and Electronics Engineers (IEEE). Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works by sending a request to pubs-permissions@ieee.org. For more information, see https://journals.ieeeauthorcenter.ieee.org/become-an-ieee-journal-author/publishing-ethics/guidelines-and-policies/post-publication-policies/-
dc.rights.urihttps://journals.ieeeauthorcenter.ieee.org/become-an-ieee-journal-author/publishing-ethics/guidelines-and-policies/post-publication-policies/-
dc.titleEMOPAIN Challenge 2020: Multimodal Pain Evaluation from Facial and Bodily Expressionsen_US
dc.typeConference paperen_US
dc.date.dateAccepted2020-03-09-
dc.identifier.doihttps://doi.org/10.1109/FG47880.2020.00078-
dc.relation.isPartOfCoRR-
dc.relation.isPartOf2020 15th IEEE International Conference on Automatic Face and Gesture Recognition (FG 2020)-
pubs.finish-date2020-11-20-
pubs.finish-date2020-11-20-
pubs.publication-statusPublished-
pubs.start-date2020-11-16-
pubs.start-date2020-11-16-
pubs.volumeabs/2001.07739-
dc.rights.holderInstitute of Electrical and Electronics Engineers (IEEE)-
Appears in Collections:Dept of Electronic and Electrical Engineering Research Papers

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