TY - GEN
T1 - Finding happiest moments in a social context
AU - Dhall, Abhinav
AU - Joshi, Jyoti
AU - Radwan, Ibrahim
AU - Goecke, Roland
PY - 2013
Y1 - 2013
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=84875911112&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-37444-9_48
DO - 10.1007/978-3-642-37444-9_48
M3 - Conference contribution
SN - 9783642374432
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 613
EP - 626
BT - Computer Vision, ACCV 2012 - 11th Asian Conference on Computer Vision, Revised Selected Papers
T2 - 11th Asian Conference on Computer Vision, ACCV 2012
Y2 - 5 November 2012 through 9 November 2012
ER -