计算机工程与应用 ›› 2007, Vol. 43 ›› Issue (25): 244-245.

• 工程与应用 • 上一篇    下一篇

基于分类器联合的表情识别

黄 勇1,3,应自炉1,2   

  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
    3.广西柳州运输职业技术学院 电子工程系,广西 柳州 545007
  • 收稿日期:1900-01-01 修回日期:1900-01-01 出版日期:2007-09-01 发布日期:2007-09-01
  • 通讯作者: 黄 勇

Facial expression recognition based on multiclassifier fusion

HUANG Yong1,3,YING Zi-lu1,2   

  1. 1.School of Information,Wuyi University,Jiangmen,Guangdong,529020,China
    2.School of Electronics and Information Engineering,Beihang University,Beijing 100083,China
    3.Liuzhou Transport Vocational Technical College,Liuzho,Guangxi 545007,China
  • Received:1900-01-01 Revised:1900-01-01 Online:2007-09-01 Published:2007-09-01
  • Contact: HUANG Yong

摘要: 提出了一种基于分类器联合的人脸表情识别方法。首先采用CKFD算法在双决策子空间中提取两类表情特征并融合;分别利用最近邻、最小距离和神经网络三种子分类器进行识别;最后运用模糊积分对子分类器的识别结果进行融合。基于JAFFE的实验结果表明,它是一种有效的表情识别方法。

关键词: 模糊积分, 分类器融合, 人脸表情识别

Abstract: A facial expression recognition method based on multiclassifier fusion with fuzzy integral has been proposed in this paper;First,applied the CKFD to extract two kinds of expression feature in double discriminant subspace and fuse them;Then the Nearest Neighbor(NN),Minimum Distance(MD) and Radial Basis Function Neural Network(RBFNN) have been used to classify facial expression;Finally,fuzzy integral has been applied to fuse outputs from three classifiers to get the final recognition result.Experimental result on JAFFE show that it is a valid method for facial expression recognition.

Key words: fuzzy integral, multiclassifier fusion, facial expression recognition