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基于子空间稀疏系数的表情识别方法
引用本文:朱明旱,李树涛,叶华.基于子空间稀疏系数的表情识别方法[J].计算机工程与应用,2014,50(12):33-37.
作者姓名:朱明旱  李树涛  叶华
作者单位:1.湖南文理学院 电气与信息工程学院,湖南 常德 415000 2.湖南大学 电气与信息工程学院,长沙 410082
基金项目:湖南省自然科学基金(No.12JJ3061);湖南省优秀青年基金(No.108074).
摘    要:提出了一种运用SRC(Sparse Representation based Classification)在个体子空间里,进行表情识别的新方法。用Gabor滤波器,提取表情图像的特征。进行稀疏分解,得到稀疏表示系数。根据稀疏系数确定待测图像所在的子空间,在子空间里,完成表情识别。这种方法较好地避免了不同个体对表情识别的干扰,从而提高了表情识别的正确率。在Cohn-Kanade和JAFFE人脸库上的表情识别实验表明,该方法对表情识别非常有效。

关 键 词:表情识别  稀疏表示  Gabor滤波  子空间  

Expression recognition method based on sparse coefficients in subspace
ZHU Minghan,LI Shutao,YE Hua.Expression recognition method based on sparse coefficients in subspace[J].Computer Engineering and Applications,2014,50(12):33-37.
Authors:ZHU Minghan  LI Shutao  YE Hua
Affiliation:1.College of Electrical and Information Engineering, Hunan University of Arts and Science, Changde, Hunan 415000, China 2.College of Electrical and Information Engineering, Hunan University, Changsha 410082, China
Abstract:A novel method to recognize facial expression in individual subspace using SRC(Sparse Representation based Classification)is proposed. Gabor filter is used to extract features of test expression image. The sparse representation coefficients of test image are gained by sparse decomposition. The individual subspace where test image lies in is found according to its sparse representation coefficients and its expression category is recognized in the subspace. The method eliminates preferably the disturbance of object without same identity to expression recognition. So recognition rates of expressions have been improved effectively. Experiments on the Cohn-Kanade face database and JAFFE face database show the proposed method achieves high performance to expression recognition.
Keywords:expression recognition  sparse representation  Gabor filtering  subspace
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