EmotiW 2020: driver gaze, group emotion, student engagement and physiological signal based challenges

dc.contributor.author	Dhall, A.
dc.contributor.author	Sharma, G.
dc.contributor.author	Goecke, R.
dc.contributor.author	Gedeon, T.
dc.date.accessioned	2021-07-02T00:05:31Z
dc.date.available	2021-07-02T00:05:31Z
dc.date.issued	2021-07-02
dc.identifier.uri	http://localhost:8080/xmlui/handle/123456789/1961
dc.description.abstract	This paper introduces the Eighth Emotion Recognition in the Wild (EmotiW) challenge. EmotiW is a benchmarking effort run as a grand challenge of the 22nd ACM International Conference on Multimodal Interaction 2020. It comprises of four tasks related to automatic human behavior analysis: a) driver gaze prediction; b) audio-visual group-level emotion recognition; c) engagement prediction in the wild; and d) physiological signal based emotion recognition. The motivation of EmotiW is to bring researchers in affective computing, computer vision, speech processing and machine learning to a common platform for evaluating techniques on a test data. We discuss the challenge protocols, databases and their associated baselines.	en_US
dc.language.iso	en_US	en_US
dc.subject	Affective computing	en_US
dc.subject	automatic human behavior analysis	en_US
dc.subject	group emotions	en_US
dc.subject	driver gaze prediction	en_US
dc.subject	student engagement	en_US
dc.title	EmotiW 2020: driver gaze, group emotion, student engagement and physiological signal based challenges	en_US
dc.type	Article	en_US