A Novel Features Extracting Technique Useing Location in Face Recognition
In PCA for the face recognition technique, computing the eigenvalues of the image matrix is the first step. Then these eigenvalues are sorted in descending order. A certain number of vectors, which correspond with these eigenvalues, are chosen by descending order and regarded as features of the face. Furthermore, these features show the whole images characters. There are differences between the images features and the faces. In this paper, a novel method based on face facial features specific positioning is proposed. This method consists of four steps: i) Locating the eyes and the middle line of the face, ii) Finding the areas of five sense organs by the faces symmetry, iii) Dimension reduction to each selected area using PCA, iv) Creating the transformation matrix for SVM classification. The recognition rate of this method is higher than the old methods. This suggests that these features from new method are more representative the real face features than old method.
face recognition PCA face partitioning feature extrication SVM
Gao Da-peng Zhu Qing-xing Yang Xing-jiang Li Chao-rong
Deptment of Computer Science and Engineering,University of Electronic Science and Technology of Chin Deptment of Computer Science and Engineering,University of Electronic Science and Technology of Chin
国际会议
杭州
英文
585-588
2012-03-23（万方平台首次上网日期，不代表论文的发表时间）