基于全局光流特征的微表情识别<sup>*</sup>

doi:10.16451/j.cnki.issn1003-6059.201608011

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Abstract The global optical flow feature extraction algorithm based on gradient is studied to improve the effect of micro-expression recognition. To solve the problem of large displacement between fine images, the multi-resolution strategy is introduced to slice the images, and the iterative reweighted least squares method is used to optimize the objective function layer by layer. Thus, the optimal optical flow is obtained, and the accuracy of motion tracking is ensured. To reflect the action differences in key parts of faces, a partition feature statistic method is proposed. The optical flow image is divided into a number of rectangular regions and in these regions the optical flow motion is concluded. Consequently, the effectiveness of the feature is enhanced. The experimental results show that overall recognition accuracy and discrimination of emotion categories are significantly improved.

Key words： Micro-expression Feature Extraction Optical Flow Recognition

Received: 18 January 2016

Fund:Supported by Key Project of Science and Technology Development Plan for Jilin Province (No.20071152)

About author:: (ZHANG Xuange, born in 1986, master student. His research interests include pattern recognition and machine vision.)(TIAN Yantao(Corresponding author), born in 1958, Ph.D., professor. His research interests include modeling, control and optimization of complex systems.)(YAN Fei, born in 1987, Ph.D. candidate. His research interests include pattern recognition.)(WANG Meiqian, born in 1991, master student. Her research interests include bionics and control.)

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	ZHANG Xuange
	TIAN Yantao
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	WANG Meiqian

Cite this article:

ZHANG Xuange,TIAN Yantao,YAN Fei等. Micro-expression Recognition Based on Global Optical Flow Feature[J]. , 2016, 29(8): 760-768.

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http://manu46.magtech.com.cn/Jweb_prai/EN/10.16451/j.cnki.issn1003-6059.201608011 OR http://manu46.magtech.com.cn/Jweb_prai/EN/Y2016/V29/I8/760

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