Finding happiest moments in a social context

Abhinav Dhall, Jyoti Joshi, Ibrahim Radwan, Roland Goecke

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

32 Citations (Scopus)


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
Number of pages14
EditionPART 2
Publication statusPublished - 11 Apr 2013
Externally publishedYes
EventAsian Conference on Computer Vision 2012 - Daejeon, Korea, South
Duration: 5 Nov 20129 Nov 2012
Conference number: 11th (Proceedings)

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


ConferenceAsian Conference on Computer Vision 2012
Abbreviated titleACCV 2012
Country/TerritoryKorea, South
Internet address

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