Deep Neural Networks with Relativity Learning for facial expression recognition

Yanan Guo*, Dapeng Tao, Jun Yu, Hao Xiong, Yaotang Li, Dacheng Tao

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contribution

28 Citations (Scopus)

Abstract

Facial expression recognition aims to classify facial expression as one of seven basic emotions including 'neutral'. This is a difficult problem due to the complexity and subtlety of human facial expressions, but the technique is needed in important applications such as social interaction research. Deep learning methods have achieved state-of-the-art performance in many tasks including face recognition and person re-identification. Here we present a deep learning method termed Deep Neural Networks with Relativity Learning (DNNRL), which directly learns a mapping from original images to a Euclidean space, where relative distances correspond to a measure of facial expression similarity. DNNRL updates the model parameters according to sample importance. This strategy results in an adjustable and robust model. Experiments on two representative facial expression datasets (FER-2013 and SFEW 2.0) are performed to demonstrate the robustness and effectiveness of DNNRL.

Original languageEnglish
Title of host publication2016 IEEE International Conference on Multimedia and Expo Workshops (ICMEW)
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Pages1-6
Number of pages6
ISBN (Electronic)9781509015528
ISBN (Print)9781509015535
DOIs
Publication statusPublished - 22 Sep 2016
Externally publishedYes
Event2016 IEEE International Conference on Multimedia and Expo Workshop, ICMEW 2016 - Seattle, United States
Duration: 11 Jul 201615 Jul 2016

Publication series

NameIEEE International Conference on Multimedia and Expo Workshops
PublisherIEEE
ISSN (Print)2330-7927

Conference

Conference2016 IEEE International Conference on Multimedia and Expo Workshop, ICMEW 2016
CountryUnited States
CitySeattle
Period11/07/1615/07/16

Keywords

  • Convolutional neural network
  • Deep feature learning
  • Facial expression
  • Social interaction

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  • Cite this

    Guo, Y., Tao, D., Yu, J., Xiong, H., Li, Y., & Tao, D. (2016). Deep Neural Networks with Relativity Learning for facial expression recognition. In 2016 IEEE International Conference on Multimedia and Expo Workshops (ICMEW) (pp. 1-6). [7574736] (IEEE International Conference on Multimedia and Expo Workshops). Institute of Electrical and Electronics Engineers (IEEE). https://doi.org/10.1109/ICMEW.2016.7574736