We investigated how shape features in natural images influence emotions aroused in human beings. Shapes and their characteristics such as roundness, angularity, simplicity, and complexity have been postulated to affect the emotional responses of human beings in the field of visual arts and psychology. However, no prior research has modeled the dimensionality of emotions aroused by roundness and angularity. Our contributions include an in depth statistical analysis to understand the relationship between shapes and emotions. Through experimental results on the International Affective Picture System (IAPS) dataset we provide evidence for the significance of roundness-angularity and simplicity-complexity on predicting emotional content in images. We combine our shape features with other state-of-the-art features to show a gain in prediction and classification accuracy. We model emotions from a dimensional perspective in order to predict valence and arousal ratings which have advantages over modeling the traditional discrete emotional categories. Finally, we distinguish images with strong emotional content from emotionally neutral images with high accuracy.

Original languageEnglish (US)
Title of host publicationMM 2012 - Proceedings of the 20th ACM International Conference on Multimedia
PublisherAssociation for Computing Machinery
Number of pages10
ISBN (Print)9781450310895
StatePublished - 2012
Event20th ACM International Conference on Multimedia, MM 2012 - Nara, Japan
Duration: Oct 29 2012Nov 2 2012

Publication series

NameMM 2012 - Proceedings of the 20th ACM International Conference on Multimedia


Other20th ACM International Conference on Multimedia, MM 2012

All Science Journal Classification (ASJC) codes

  • Computer Graphics and Computer-Aided Design
  • Human-Computer Interaction
  • Software


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