Finding Happiest Moments in a Social Context

Abhinav Dhall, Jyoti Dhall, Ibrahim Radwan, Roland Goecke

Research output: A Conference proceeding or a Chapter in BookConference contributionpeer-review

33 Citations (Scopus)
2 Downloads (Pure)


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 publication11th Asian Conference on Computer Vision
EditorsKyoung Mu Lee, Yasuyuki Matsushita, James M Rehg, Zhanyi Hu
Place of PublicationBerlin Heidelberg
Number of pages14
ISBN (Print)9783642374432
Publication statusPublished - 2013
Event11th Asian Conference on Computer Vision - Daejeon, Daejeon, Korea, Republic of
Duration: 5 Nov 20129 Nov 2012


Conference11th Asian Conference on Computer Vision
Country/TerritoryKorea, Republic of


Dive into the research topics of 'Finding Happiest Moments in a Social Context'. Together they form a unique fingerprint.

Cite this