From individual to group-level emotion recognition: EmotiW 5.0

Abhinav Dhall, Roland Goecke, Shreya Ghosh, Jyoti Joshi, Jesse Hoey, Tom Gedeon

Research output: A Conference proceeding or a Chapter in BookConference contribution

73 Citations (Scopus)

Abstract

Research in automatic affect recognition has come a long way. This paper describes the fifth Emotion Recognition in the Wild (EmotiW) challenge 2017. EmotiW aims at providing a common benchmarking platform for researchers working on different aspects of affective computing. This year there are two sub-challenges: a) Audio-video emotion recognition and b) group-level emotion recognition. These challenges are based on the acted facial expressions in the wild and group affect databases, respectively. The particular focus of the challenge is to evaluate method in 'in the wild' settings. 'In the wild' here is used to describe the various environments represented in the images and videos, which represent real-world (not lab like) scenarios. The baseline, data, protocol of the two challenges and the challenge participation are discussed in detail in this paper.
Original languageEnglish
Title of host publicationICMI 2017 - Proceedings of the 19th ACM International Conference on Multimodal Interaction
EditorsEdward Lank, Eve Hoggan, Sriram Subramanian, Alessandro Vinciarelli, Stephen A. Brewster
Place of PublicationNew York, New York, USA
PublisherACM Press, New York, NY USA
Pages524-528
Number of pages5
ISBN (Electronic)9781450355438
ISBN (Print)9781450355438
DOIs
Publication statusPublished - 3 Nov 2017
Event19th ACM International Conference on Multimodal Interaction - Glasgow, United Kingdom
Duration: 13 Nov 201717 Nov 2017
https://icmi.acm.org/2017/

Publication series

NameICMI 2017 - Proceedings of the 19th ACM International Conference on Multimodal Interaction
Volume2017-January

Conference

Conference19th ACM International Conference on Multimodal Interaction
Abbreviated titleICMI 2017
CountryUnited Kingdom
CityGlasgow
Period13/11/1717/11/17
Internet address

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