EMOPAIN Challenge 2020: Multimodal Pain Evaluation from Facial and Bodily Expressions

• URL: http://arxiv.org/abs/2001.07739v3
• Date: Mon, 9 Mar 2020 16:14:31 GMT
• Title: EMOPAIN Challenge 2020: Multimodal Pain Evaluation from Facial and Bodily Expressions
• Authors: Joy O. Egede, Siyang Song, Temitayo A. Olugbade, Chongyang Wang, Amanda Williams, Hongying Meng, Min Aung, Nicholas D. Lane, Michel Valstar and Nadia Bianchi-Berthouze
• Abstract summary: EmoPain 2020 Challenge is the first international competition aimed at creating a uniform platform for the comparison of machine learning and multimedia processing methods. This paper presents a description of the challenge, competition guidelines, bench-marking dataset, and the baseline systems' architecture and performance.
• Score: 10.48692251648146
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: The EmoPain 2020 Challenge is the first international competition aimed at creating a uniform platform for the comparison of machine learning and multimedia processing methods of automatic 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 three sub-tasks: pain estimation from facial expressions, pain recognition from multimodal movement, and protective movement behaviour detection.

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