基于主元分析与支持向量机的人脸识别方法  

A Face Recognition Method Based on Principal Component Analysis and Support Vector Machine

作　　者：张燕昆[1] 杜平[1] 刘重庆[1] 

机构地区：[1]上海交通大学图像处理与模式识别研究所,上海200030

出　　处：《上海交通大学学报》2002年第6期884-886,共3页Journal of Shanghai Jiaotong University

摘　　要：基于支持向量机 ( SVM)在处理小样本、高维数及泛化性能强等方面的优势 ,提出了一种基于主元分析 ( PCA)与 SVM的人脸识别方法 .利用 PCA方法对人脸图像进行特征提取 ,再利用SVM与最近邻分类器相结合的策略对特征向量进行分类识别 .剑桥Based on the high performance of support vector machine(SVM) in tackling small sample size, high dimension and its good generalization, this paper proposed a face recognition method based on principal component analysis(PCA) and SVM. The PCA is used to reduce the dimension and extract the feature, then the SVM combined with the nearest distance classifier is used for classification. The ORL face database was used to test the proposed method. The experiment result shows that the method is effective.

关 键 词：人脸识别 支持向量机 主元分析 最近邻距离分类器 模式识别 特征提取 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]