Finding happiest moments in a social context

Authors:
Abhinav Dhall;Jyoti Joshi;Ibrahim Radwan;Roland Goecke
Affiliations:
IHCC Group, Research School of Computer Science, Australian National University, Australia;Vision & Sensing Group, Faculty of ISE, University of Canberra, Australia;Vision & Sensing Group, Faculty of ISE, University of Canberra, Australia;Vision & Sensing Group, Faculty of ISE, University of Canberra, Australia,IHCC Group, Research School of Computer Science, Australian National University, Australia
Venue:
ACCV'12 Proceedings of the 11th Asian conference on Computer Vision - Volume Part II
Year:
2012

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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.