• KSII Transactions on Internet and Information Systems
    Monthly Online Journal (eISSN: 1976-7277)

Micro-Expression Recognition Base on Optical Flow Features and Improved MobileNetV2

Vol. 15, No. 6, June 30, 2021
10.3837/tiis.2021.06.002, Download Paper (Free):

Abstract

When a person tries to conceal emotions, real emotions will manifest themselves in the form of micro-expressions. Research on facial micro-expression recognition is still extremely challenging in the field of pattern recognition. This is because it is difficult to implement the best feature extraction method to cope with micro-expressions with small changes and short duration. Most methods are based on hand-crafted features to extract subtle facial movements. In this study, we introduce a method that incorporates optical flow and deep learning. First, we take out the onset frame and the apex frame from each video sequence. Then, the motion features between these two frames are extracted using the optical flow method. Finally, the features are inputted into an improved MobileNetV2 model, where SVM is applied to classify expressions. In order to evaluate the effectiveness of the method, we conduct experiments on the public spontaneous micro-expression database CASME II. Under the condition of applying the leave-one-subject-out cross-validation method, the recognition accuracy rate reaches 53.01%, and the F-score reaches 0.5231. The results show that the proposed method can significantly improve the micro-expression recognition performance.


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Cite this article

[IEEE Style]
W. Xu, H. Zheng, Z. Yang and Y. Yang, "Micro-Expression Recognition Base on Optical Flow Features and Improved MobileNetV2," KSII Transactions on Internet and Information Systems, vol. 15, no. 6, pp. 1981-1995, 2021. DOI: 10.3837/tiis.2021.06.002.

[ACM Style]
Wei Xu, Hao Zheng, Zhongxue Yang, and Yingjie Yang. 2021. Micro-Expression Recognition Base on Optical Flow Features and Improved MobileNetV2. KSII Transactions on Internet and Information Systems, 15, 6, (2021), 1981-1995. DOI: 10.3837/tiis.2021.06.002.