Automatic group happiness intensity analysis

Abhinav Dhall, Roland Goecke, Tom Gedeon

Research output: Contribution to journalArticleResearchpeer-review

53 Citations (Scopus)

Abstract

The recent advancement of social media has given users a platform to socially engage and interact with a larger population. Millions of images and videos are being uploaded everyday by users on the web from different events and social gatherings. There is an increasing interest in designing systems capable of understanding human manifestations of emotional attributes and affective displays. As images and videos from social events generally contain multiple subjects, it is an essential step to study these groups of people. In this paper, we study the problem of happiness intensity analysis of a group of people in an image using facial expression analysis. A user perception study is conducted to understand various attributes, which affect a person's perception of the happiness intensity of a group. We identify the challenges in developing an automatic mood analysis system and propose three models based on the attributes in the study. An 'in the wild' image-based database is collected. To validate the methods, both quantitative and qualitative experiments are performed and applied to the problem of shot selection, event summarisation and album creation. The experiments show that the global and local attributes defined in the paper provide useful information for theme expression analysis, with results close to human perception results.

Original languageEnglish
Article number7029085
Pages (from-to)13-26
Number of pages14
JournalIEEE Transactions on Affective Computing
Volume6
Issue number1
DOIs
Publication statusPublished - 2015
Externally publishedYes

Keywords

  • Facial expression recognition
  • group mood
  • unconstrained conditions

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