Face Recognition Using Spatially Smooth and Maximum Minimum Value of Manifold Preserving  

作　　者：WEN Hao WEN Youkui 

机构地区：[1]School of Information and Control Engineering, Xi'an University of Architecture Technology, Xi'an 710055, China [2]Xidian University, Xi'an 710071, China

出　　处：《Chinese Journal of Electronics》2013年第1期71-75,共5页电子学报（英文版）

摘　　要：Subspace face recognition methods have attracted considerable interests in recent years. However, the accuracy rates of previous methods are not high. The reason is that the manifold of face image data is not uti-lized sufficiently and some patitcular characters of the in-dividual image are neglected in these methods. Thus a new method to form graph of data is proposed in this paper and is used to develop two face recognition algorithms. The maximum minimum value of manifold can be preserved based on the new graph. At the same time the pixels cor-relation in individual image is considered sufficient under the constrain of spatial smoothness in the two developed algorithms. Therefore, the right recognition rates are en-hanced by the two proposed algorithms. This is further confirmed by experiments.

关 键 词：Manifold learning Face recognition Spa-tially smooth Subspace learning. 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术] TN911.7[自动化与计算机技术—计算机科学与技术]