EmotiW 2019: automatic emotion, engagement and cohesion prediction tasks

dc.contributor.author	Dhall, A.
dc.contributor.author	Ghosh, S.
dc.contributor.author	Goecke, R.
dc.contributor.author	Gedeon, T.
dc.date.accessioned	2019-11-27T13:08:22Z
dc.date.available	2019-11-27T13:08:22Z
dc.date.issued	2019-11-27
dc.identifier.uri	http://localhost:8080/xmlui/handle/123456789/1399
dc.description.abstract	This paper describes the Seventh Emotion Recognition in the Wild (EmotiW) Challenge. The EmotiW benchmarking platform provides researchers with an opportunity to evaluate their methods on affect labelled data. This year EmotiW 2019 encompasses three sub-challenges: a) Group-level cohesion prediction; b) Audio-Video emotion recognition; and c) Student engagement prediction. We discuss the databases used, the experimental protocols and the baselines.	en_US
dc.language.iso	en_US	en_US
dc.subject	Affect recognition	en_US
dc.subject	Multimodal Analysis	en_US
dc.subject	Neural networks	en_US
dc.subject	Emotion Recognition	en_US
dc.title	EmotiW 2019: automatic emotion, engagement and cohesion prediction tasks	en_US
dc.type	Article	en_US