修正的最大散度差鉴别分析及人脸识别

刘永俊; 陈才扣; 王正群

doi:10.3724/SP.J.1146.2006.00811

修正的最大散度差鉴别分析及人脸识别

doi: 10.3724/SP.J.1146.2006.00811

刘永俊^{①②;陈才扣},
陈才扣,
王正群

基金项目:

江苏省高校自然科学基金(05KJB520152)和江苏省博士后科研资助计划项目资助课题

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出版历程
- 收稿日期: 2006-06-12
- 修回日期: 2007-04-02
- 刊出日期: 2008-01-19

Modified Maximum Scatter-difference Discriminant Analysis and Face Recognition

摘要

摘要: 针对传统的Fisher线性鉴别分析在人脸这样的多类高维小样本模式的分类中存在的小样本问题和次优性问题，该文提出了一种基于修正的最大散度差鉴别准则的线性鉴别分析方法。该方法对最大散度差鉴别准则中散布矩阵的构造加以修正，采用新的修正的最大散度差鉴别准则函数。该方法从理论上为有效地解决传统的Fisher线性鉴别分析在人脸识别中存在的这两大难题提供了有效的途径。最后，在ORL，AR标准人脸库上的实验结果验证了该算法的有效性。
- 人脸识别; Fisher线性鉴别分析; 最大散度差鉴别分析
Abstract: Cosidering the so-called Small Sample Size(SSS) problem in nature and the inferior problem in traditional Fisher linear discriminant analysis, a new method of feature extraction based on modified maximum scatter-difference criterion is developed in this paper. The method gives an effective way to resolve two difficulties of the traditional Fisher linear discriminant analysis theoretically in face recognition. Finally, extensive experiments performed on ORL and AR face database verify the effectiveness of the proposed method.

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参考文献(1)

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