The more the merrier: Analysing the affect of a group of people in images

• Published in: 2015 11th IEEE International Conference and Workshops on Automatic Face and Gesture Recognition (FG) Vol. 1; pp. 1 - 8
• Main Authors: Dhall, Abhinav, Joshi, Jyoti, Sikka, Karan, Goecke, Roland, Sebe, Nicu
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.05.2015
• Subjects: Computational modeling; Context; Gold; Kernel; Mood; Videos
• DOI: 10.1109/FG.2015.7163151

The recent advancement of social media has given users a platform to socially engage and interact with a global population. With millions of images being uploaded onto social media platforms, there is an increasing interest in inferring the emotion and mood display of a group of people in images. Automatic affect analysis research has come a long way but has traditionally focussed on a single subject in a scene. In this paper, we study the problem of inferring the emotion of a group of people in an image. This group affect has wide applications in retrieval, advertisement, content recommendation and security. The contributions of the paper are: 1) a novel emotion labelled database of groups of people in images; 2) a Multiple Kernel Learning based hybrid affect inference model; 3) a scene context based affect inference model; 4) a user survey to better understand the attributes that affect the perception of affect of a group of people in an image. The detailed experimentation validation provides a rich baseline for the proposed database.