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WANG Shuliang, CHI Hehua, YUAN Ziqiang, GENG Jing. Emotion Recognition Using Cloud Model[J]. Chinese Journal of Electronics, 2019, 28(3): 470-474. DOI: 10.1049/cje.2018.09.020
Citation: WANG Shuliang, CHI Hehua, YUAN Ziqiang, GENG Jing. Emotion Recognition Using Cloud Model[J]. Chinese Journal of Electronics, 2019, 28(3): 470-474. DOI: 10.1049/cje.2018.09.020
shu

Emotion Recognition Using Cloud Model

  • 1.

    School of Computer Science, Wuhan University, Wuhan 430079, China;

  • 2.

    School of software, Beijing Institute of Technology, Beijing 100081, China;

  • 3.

    Goergen Institute for Data Science, University of Rochester, Rochester NY 14627, USA

Funds: This work is supported by the National Key Research and Development Plan of China (No.2016YFC0803000, No.2016YFB0502604) and National Natural Science Fund of China (No.61472039).
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  • Corresponding author:

    CHI Hehua (corresponding author) is a Ph.D. candidate in Wuhan University and also a graduate student in University of Rochester. (Email:hchi3@ur.rochester.edu)

  • Received Date: May 15, 2017
  • Published Date: May 09, 2019
    Graphical Abstract
    • Abstract
  • Emotions often facilitate interactions among human beings, but the big variation of human emotional states make a negative effect on the reliable emotion recognition. We propose a novel algorithm to extract common features for each type of emotional states which can reliably present human emotions. To uncover the common features from uncertain emotional states, the backward cloud generator is used to discover {Ex, En, He} by integrating randomness and fuzziness. Finally, the proposed method for emotion recognition is verified on the common facial expression datasets, the Extended Cohn-Kanade (CK+) dataset and the Japanese female facial expression (JAFFE). The results are satisfactory, which shows cloud model is potentially useful in pattern recognition and machines learning.
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    • References (22)
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