From individual to group-level emotion recognition: EmotiW 5.0

Abhinav Dhall, Roland Goecke, Shreya Ghosh, Jyoti Joshi, Jesse Hoey, Tom Gedeon

Research output: Chapter in Book/Report/Conference proceedingConference PaperOther

129 Citations (Scopus)


Research in automatic affect recognition has come a long way. This paper describes the fifth Emotion Recognition in the Wild (EmotiW) challenge 2017. EmotiW aims at providing a common benchmarking platform for researchers working on different aspects of affective computing. This year there are two sub-challenges: A) Audio-video emotion recognition and b) group-level emotion recognition. These challenges are based on the acted facial expressions in the wild and group affect databases, respectively. The particular focus of the challenge is to evaluate method in 'in the wild' settings. 'In the wild' here is used to describe the various environments represented in the images and videos, which represent real-world (not lab like) scenarios. The baseline, data, protocol of the two challenges and the challenge participation are discussed in detail in this paper.

Original languageEnglish
Title of host publicationProceedings of the 19th ACM International Conference on Multimodal Interaction
EditorsEdward Lank, Eve Hoggan, Sriram Subramanian, Alessandro Vinciarelli, Stephen A. Brewster
Place of PublicationNew York NY USA
PublisherAssociation for Computing Machinery (ACM)
Number of pages5
ISBN (Electronic)9781450355438
Publication statusPublished - 2017
Externally publishedYes
EventEmotion Recognition in the Wild Challenge 2017 - Glasgow, United Kingdom
Duration: 17 Nov 201717 Nov 2017
Conference number: 5th


ConferenceEmotion Recognition in the Wild Challenge 2017
Abbreviated titleEmotiW 2017
Country/TerritoryUnited Kingdom
Internet address


  • Affect analysis in the wild
  • Audio-video data corpus
  • Emotion recognition
  • Facial expression challenge
  • Group-level emotion recognition

Cite this