基于核的Foley-Sammon鉴别分析与人脸识别  

Kernel-Based Foley-Sammon Discriminant Analysis and Face Recognition

作　　者：高秀梅[1] 杨静宇[1] 金忠[1] 陈才扣[1] 

机构地区：[1]南京理工大学计算机科学与技术系,南京210094

出　　处：《计算机辅助设计与图形学学报》2004年第7期962-967,共6页Journal of Computer-Aided Design & Computer Graphics

基　　金：国家自然科学基金 ( 60 0 72 0 3 4)资助

摘　　要：通过建立基于核的Foley Sammon鉴别分析 (KFSDA)的两个等价模型 ,并分析这两个等价模型的解之间的关系 ,从理论上给出KFSDA模型的具体求解方法 分析表明 ,基于核的Foley Sammon鉴别分析保留了FSDA能明显降低样本特征之间冗余信息的优点 ,更重要的是该方法能够有效地抽取样本的非线性特征 ,是对FSDA的进一步拓展Through implementing two equivalent models of kernel based Foley Sammon discriminant analysis (KFSDA) and studying the relationship between the solutions of these two models, a new approach of solving the KFSDA model is presented and proved Analysis shows that KFSDA retains FSDA's advantage of distinctly reducing the redundant information among components of the pattern samples, and more importantly, it can extract nonlinear features effectively, thus greatly enhancing the capability of FSDA Experimental results on ORL face database indicate that the proposed method is valid

关 键 词：基于核的F-S鉴别分析 最佳鉴别矢量集 特征抽取 人脸识别 

分 类 号：TP391.4[自动化与计算机技术—计算机应用技术]