.png){kind=icon}
Return
Automatic Group Happiness Intensity Analysis
.png){kind=icon}
PRE
AI
DOI：10.1109/TAFFC.2015.2397456.png)
.png){kind=icon}
.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
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.
Keywords:
Facial expression recognition
group mood
unconstrained conditions
Journal
IF:
9.8
Papers:
1.4K
Citations:
9.1K
Organization
Cited Papers
ShareSaveShareSaveA review of the Irish crustal structure and signatures from the Caledonian and Variscan Orogenies.png)
Terra Nova
Terra NovaIF0
PREAI
ShareSave
ShareSaveShareSaveShareSaveShareSave
View more