Micro-Expression Recognition based on 2D Gabor Filter and Sparse Representation

2016 International Conference on Communication, Image and Signal Processing

物理学;无线电电子学;计算机科学

Zheng, Hao^1,2,3

Key Laboratory of Trusted Cloud Computing and Big Data Analysis, School of Information Engineering, Nanjing XiaoZhuang University, Nanjing, China^1

MOE Key Laboratory of Computer Network and Information Integration, School of Computer Science and Engineering, Southeast University, Nanjing, China^2

State Key Laboratory for Novel Software Technology, Nanjing University, Nanjing, China^3

关键词: 2-D Gabor filter;    Facial Expressions;    Micro-expressions;    Sparse approximations;    Sparse representation;   

Others  :  https://iopscience.iop.org/article/10.1088/1742-6596/787/1/012013/pdf
DOI  :  10.1088/1742-6596/787/1/012013

学科分类：计算机科学（综合）

来源: IOP

【 摘 要 】

Micro-expression recognition is always a challenging problem for its quick facial expression. This paper proposed a novel method named 2D Gabor filter and Sparse Representation (2DGSR) to deal with the recognition of micro-expression. In our method, 2D Gabor filter is used for enhancing the robustness of the variations due to increasing the discrimination power. While the sparse representation is applied to deal with the subtlety, and cast recognition as a sparse approximation problem. We compare our method to other popular methods in three spontaneous micro-expression recognition databases. The results show that our method has more excellent performance than other methods.