From individual to group-level emotion recognition: Emoti W 5.0

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

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

    161 Citations (Scopus)

    Abstract

    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 publicationICMI 2017 - Proceedings of the 19th ACM International Conference on Multimodal Interaction
    EditorsEdward Lank, Eve Hoggan, Sriram Subramanian, Alessandro Vinciarelli, Stephen A. Brewster
    PublisherAssociation for Computing Machinery, Inc
    Pages524-528
    Number of pages5
    ISBN (Electronic)9781450355438
    DOIs
    Publication statusPublished - 3 Nov 2017
    Event19th ACM International Conference on Multimodal Interaction, ICMI 2017 - Glasgow, United Kingdom
    Duration: 13 Nov 201717 Nov 2017

    Publication series

    NameICMI 2017 - Proceedings of the 19th ACM International Conference on Multimodal Interaction
    Volume2017-January

    Conference

    Conference19th ACM International Conference on Multimodal Interaction, ICMI 2017
    Country/TerritoryUnited Kingdom
    CityGlasgow
    Period13/11/1717/11/17

    Fingerprint

    Dive into the research topics of 'From individual to group-level emotion recognition: Emoti W 5.0'. Together they form a unique fingerprint.

    Cite this