@inproceedings{be93010a90be4f8ea15dff8cab62518b,
title = "The more the merrier: Analysing the affect of a group of people in images",
abstract = "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.",
author = "Abhinav Dhall and Jyoti Joshi and Karan Sikka and Roland Goecke and Nicu Sebe",
note = "Publisher Copyright: {\textcopyright} 2015 IEEE.; 11th IEEE International Conference and Workshops on Automatic Face and Gesture Recognition, FG 2015 ; Conference date: 04-05-2015 Through 08-05-2015",
year = "2015",
month = jul,
day = "17",
doi = "10.1109/FG.2015.7163151",
language = "English",
series = "2015 11th IEEE International Conference and Workshops on Automatic Face and Gesture Recognition, FG 2015",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "2015 11th IEEE International Conference and Workshops on Automatic Face and Gesture Recognition, FG 2015",
address = "United States",
}