EmotiW 2018: audio-video, student engagement and group-level affect prediction

Abhinav Dhall, Amanjot Kaur, Roland Goecke, Tamás (Tom) Gedeon

Research output: Chapter in Book/Report/Conference proceedingConference PaperOtherpeer-review

Abstract

This paper details the sixth Emotion Recognition in the Wild (EmotiW) challenge. EmotiW 2018 is a grand challenge in the ACM International Conference on Multimodal Interaction 2018, Colarado, USA. The challenge aims at providing a common platform to researchers working in the affective computing community to benchmark their algorithms on ‘in the wild’ data. This year EmotiW contains three sub-challenges: a) Audio-video based emotion recognition; b) Student engagement prediction; and c) Group-level emotion recognition.
The databases, protocols and baselines are discussed in detail.
Original languageEnglish
Title of host publicationProceedings of the 20th ACM International Conference on Multimodal Interaction
EditorsEmily Mower Provost, Mohammad Soleymani, Marcelo Worsley
Place of PublicationNew York NY USA
PublisherAssociation for Computing Machinery (ACM)
Pages653-656
Number of pages4
ISBN (Electronic)9781450356923
Publication statusPublished - 2018
Externally publishedYes
EventInternational Conference on Multimodal Interfaces 2018 - Boulder, United States of America
Duration: 16 Oct 201920 Oct 2019
Conference number: 20th
https://icmi.acm.org/2018/

Conference

ConferenceInternational Conference on Multimodal Interfaces 2018
Abbreviated titleICMI 2018
CountryUnited States of America
CityBoulder
Period16/10/1920/10/19
Internet address

Keywords

  • Emotion Recognition
  • Affective Computing

Cite this

Dhall, A., Kaur, A., Goecke, R., & Gedeon, T. T. (2018). EmotiW 2018: audio-video, student engagement and group-level affect prediction. In E. Mower Provost, M. Soleymani, & M. Worsley (Eds.), Proceedings of the 20th ACM International Conference on Multimodal Interaction (pp. 653-656). Association for Computing Machinery (ACM). https://dl.acm.org/citation.cfm?id=3264993