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dc.contributor.authorDhall, A.-
dc.contributor.authorSharma, G.-
dc.contributor.authorGoecke, R.-
dc.contributor.authorGedeon, T.-
dc.date.accessioned2021-07-02T00:05:31Z-
dc.date.available2021-07-02T00:05:31Z-
dc.date.issued2021-07-02-
dc.identifier.urihttp://localhost:8080/xmlui/handle/123456789/1961-
dc.description.abstractThis 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.isoen_USen_US
dc.subjectAffective computingen_US
dc.subjectautomatic human behavior analysisen_US
dc.subjectgroup emotionsen_US
dc.subjectdriver gaze predictionen_US
dc.subjectstudent engagementen_US
dc.titleEmotiW 2020: driver gaze, group emotion, student engagement and physiological signal based challengesen_US
dc.typeArticleen_US
Appears in Collections:Year-2020

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