计算机工程与应用 ›› 2009, Vol. 45 ›› Issue (29): 180-183.DOI: 10.3778/j.issn.1002-8331.2009.29.053

• 图形、图像、模式识别 • 上一篇    下一篇

基于局部二元模式的面部表情识别研究

应自炉1,2,方谢燕1   

  1. 1.五邑大学 信息学院,广东 江门 529020
    2.北京航空航天大学 电子信息工程学院,北京 100083
  • 收稿日期:2008-05-29 修回日期:2008-08-25 出版日期:2009-10-11 发布日期:2009-10-11
  • 通讯作者: 应自炉

Facial expression recognition research based on local binary pattern

YING Zi-lu1,2,FANG Xie-yan1   

  1. 1.School of Information,Wuyi University,Jiangmen,Guangdong 529020,China
    2.School of Electronics and Information Engineering,Beihang University,Beijing 100083,China
  • Received:2008-05-29 Revised:2008-08-25 Online:2009-10-11 Published:2009-10-11
  • Contact: YING Zi-lu

摘要: 提出了一种基于局部二元模式(Local Binary Pattern,LBP)与支持向量机(SVM)相结合的面部表情识别方法。使用LBP算子对图像进行处理,对图像的模式进行统计形成面部表情特征;使用线性判别分析对表情特征进行降维处理;采用支持向量机对面部表情进行分类。用Matlab实现了上述方法,并在日本女性人脸表情(JAFFE)数据库上测试,取得了70.95%的识别率。

关键词: 面部表情识别, 局部二元模式, 线性判别分析, 支持向量机

Abstract: A novel approach to facial expression recognition based on the combination of Local Binary Pattern(LBP) and Support Vector Machine(SVM) is proposed.First,the algorithm processes facial expression images with LBP operator and then facial expression features are formed by statistics of image’s LBPs.Then Linear Discrimination Analysis(LDA) method is used for feature dimension reduction and SVM for classification.Finally,the algorithm is implemented with Matlab and experimented in Japanese Female Facial Expression database(JAFFE database).A recognition rate of 70.95% is obtained and shows the effectiveness of the proposed algorithm.

Key words: facial expression recognition, Local Binary Pattern(LBP), Linear Discrimination Analysis(LDA), Support Vector Machine(SVM)

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