Finding happiest moments in a social context

Abhinav Dhall*, Jyoti Joshi, Ibrahim Radwan, Roland Goecke

*Corresponding author for this work

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

    36 Citations (Scopus)

    Abstract

    We study the problem of expression analysis for a group of people. Automatic facial expression analysis has seen much research in recent times. However, little attention has been given to the estimation of the overall expression theme conveyed by an image of a group of people. Specifically, this work focuses on formulating a framework for happiness intensity estimation for groups based on social context information. The main contributions of this paper are: a) defining automatic frameworks for group expressions; b) social features, which compute weights on expression intensities; c) an automatic face occlusion intensity detection method; and d) an 'in the wild' labelled database containing images having multiple subjects from different scenarios. The experiments show that the global and local contexts provide useful information for theme expression analysis, with results similar to human perception results.

    Original languageEnglish
    Title of host publicationComputer Vision, ACCV 2012 - 11th Asian Conference on Computer Vision, Revised Selected Papers
    Pages613-626
    Number of pages14
    EditionPART 2
    DOIs
    Publication statusPublished - 2013
    Event11th Asian Conference on Computer Vision, ACCV 2012 - Daejeon, Korea, Republic of
    Duration: 5 Nov 20129 Nov 2012

    Publication series

    NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
    NumberPART 2
    Volume7725 LNCS
    ISSN (Print)0302-9743
    ISSN (Electronic)1611-3349

    Conference

    Conference11th Asian Conference on Computer Vision, ACCV 2012
    Country/TerritoryKorea, Republic of
    CityDaejeon
    Period5/11/129/11/12

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