一种对称散布矩阵空间的人脸识别方法  

Face recognition approach based on symmetrical scatter matrix space

作　　者：段旭[1] 张绛丽[1] 

机构地区：[1]江苏科技大学计算机科学与工程学院,江苏镇江212003

出　　处：《计算机应用研究》2010年第4期1557-1559,共3页Application Research of Computers

摘　　要：为有效解决小样本问题,从线性子空间的角度出发,构造了一种矩阵变换,得到了类内散布矩阵的另一个对称线性子空间;通过对两个子空间的分别求解,从而得到样本有效的鉴别信息。该方法有效地解决了传统Fisher鉴别分析方法中的最终特征维数受类别数限制的问题。在NUST603和ORL人脸数据库上的实验结果验证了算法的有效性。To solve the small sample size problem efficiently,proposed a matrix transform on the basis of linear subspace theory,by which constructed a new linear symmetrical subspace of within-class scatter matrix.By the Fisher＇s discriminant crite-rion,derived two solution spaces from the within-class scatter matrix and respectively utilized its corresponding symmetrical subspace to obtain the efficient discriminatory information of the samples.Therefore,overcame the shortcoming of final dimensionality of features obtained by Fisher＇s discriminant analysis was limited by the number of classes.Experimental results conducted on the NUST603 and ORL face databases demonstrate the effectiveness of the proposed method.

关 键 词：特征抽取 线性鉴别分析 对称散布子空间 小样本问题 人脸识别 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]