%0 Journal Article
%T A New Kernel Discriminant Analysis Algorithm and its Application to Face Recognition<br>一种新的核线性鉴别分析算法及其在人脸识别上的应用
%A ZHENG Yu-Jie
%A YANG Jing-Yu
%A WU Xiao-Jun
%A WANG Wei-Dong
%A ZHANG Li-Li
%A <br>郑宇杰
%A 杨静宇
%A 吴小俊
%A 王卫东
%A 张丽丽
%J 计算机科学
%D 2006
%I 
%X Kernel Fisher discriminative analysis(KFD)algorithm based on kernel trick has been one of the effective nonlinear feature extraction methods.But all previous nonlinear feature extraction methods based on KFD algorithm which procedures are based on solving binary classification problem.How to extract effective discriminative information from overlapping(outlier)samples is still open.In this paper,a new KFD algorithm named fuzzy kernel discriminative analysis(FKFD)is proposed.In the proposed algorithm,fuzzy K-nearest neighbor(FKNN)algorithm is incorporated into the process of KFD algorithm and the corresponding fuzzy membership degrees are gained.Therefore,distribution information of samples is embedded in the proposed algorithm through fuzzy membership degrees.Experimental results on ORL face database demonstrate the effectiveness of the proposed algorithm.
%K Kernel trick
%K Kernel Fisher discriminative analysis
%K Fuzzy kernel Fisher discriminative analysis
%K Feature extraction
%K Face recognition<br>核策略
%K 核Fisher鉴别分析
%K 模糊核Fisher鉴别分析
%K 特征提取
%K 人脸识别
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=64A12D73428C8B8DBFB978D04DFEB3C1&aid=308EC58DAAD6E0F4&yid=37904DC365DD7266&vid=27746BCEEE58E9DC&iid=DF92D298D3FF1E6E&sid=E089FDF3CDAE8561&eid=6ED15D8DCB279BC4&journal_id=1002-137X&journal_name=计算机科学&referenced_num=1&reference_num=13