User-Centric Affective Computing of Image Emotion Perceptions

Authors

  • Sicheng Zhao Harbin Institute of Technology
  • Hongxun Yao Harbin Institute of Technology
  • Wenlong Xie Harbin Institute of Technology
  • Xiaolei Jiang Harbin Institute of Technology

DOI:

https://doi.org/10.1609/aaai.v30i1.9947

Keywords:

Affective computing, Image emotion, Personalized perception, Hypergraph learning

Abstract

We propose to predict the personalized emotion perceptions of images for each viewer. Different factors that may influence emotion perceptions, including visual content, social context, temporal evolution, and location influence are jointly investigated via the presented rolling multi-task hypergraph learning. For evaluation, we set up a large scale image emotion dataset from Flickr, named Image-Emotion-Social-Net, with over 1 million images and about 8,000 users. Experiments conducted on this dataset demonstrate the superiority of the proposed method, as compared to state-of-the-art.

AAAI 2016 Proceedings Cover

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Published

2016-03-05

How to Cite

Zhao, S., Yao, H., Xie, W., & Jiang, X. (2016). User-Centric Affective Computing of Image Emotion Perceptions. Proceedings of the AAAI Conference on Artificial Intelligence, 30(1). https://doi.org/10.1609/aaai.v30i1.9947

Issue

Vol. 30 No. 1 (2016): Thirtieth AAAI Conference on Artificial Intelligence

Section

Student Abstracts and Posters