EmotiW 2019: Automatic emotion, engagement and cohesion prediction tasks

Abhinav Dhall, Shreya Ghosh, Roland Goecke, Tom Gedeon

Research output: A Conference proceeding or a Chapter in BookConference contributionpeer-review

69 Citations (Scopus)

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.

Original languageEnglish
Title of host publicationICMI 2019 - Proceedings of the 2019 International Conference on Multimodal Interaction
EditorsWen Gao, Helen Mei Ling Meng, Matthew Turk, Susan R. Fussell, Bjorn Schuller, Bjorn Schuller, Yale Song, Kai Yu
Place of PublicationNew York
PublisherAssociation for Computing Machinery, Inc
Pages546-550
Number of pages5
ISBN (Electronic)9781450368605
DOIs
Publication statusPublished - 14 Oct 2019
Event21st ACM International Conference on Multimodal Interaction, ICMI 2019 - Suzhou, China
Duration: 14 Oct 201918 Oct 2019

Publication series

NameICMI 2019 - Proceedings of the 2019 International Conference on Multimodal Interaction

Conference

Conference21st ACM International Conference on Multimodal Interaction, ICMI 2019
Country/TerritoryChina
CitySuzhou
Period14/10/1918/10/19

Fingerprint

Dive into the research topics of 'EmotiW 2019: Automatic emotion, engagement and cohesion prediction tasks'. Together they form a unique fingerprint.

Cite this