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一种新的正交保局投影人脸识别方法
引用本文:李瑞东,余党军,陈偕雄.一种新的正交保局投影人脸识别方法[J].科技通报,2007,23(5):702-704.
作者姓名:李瑞东  余党军  陈偕雄
作者单位:1. 金华职业技术学院,信息工程学院,金华,321017
2. 浙江大学,信息学院,杭州,310028
摘    要:针对人脸识别中判别特征的提取问题,提出了一种新的人脸识别算法—Schur正交保局投影(Schur-OLPP)。该方法在保局投影(LPP)的基础上引入Schur分解,求取最佳正交投影矩阵,充分提取样本的判别特征。本文采用最小近邻分类器估算识别率。在Yale人脸库以及AR人脸库的测试结果表明,在姿态、光照、表情、时间变化的情况下,Schur-OLPP都具有较好的识别率。

关 键 词:正交保局投影  Schur分解  判别信息提取  人脸识别
文章编号:1001-7119(2007)05-0702-03
收稿时间:2006-09-24
修稿时间:2006-09-24

A new Alternative formulation of orthogonal LPP with Application to Face Recognition
LI Rui-dong,YU Dang-jun,CHENG Xie-xiong.A new Alternative formulation of orthogonal LPP with Application to Face Recognition[J].Bulletin of Science and Technology,2007,23(5):702-704.
Authors:LI Rui-dong  YU Dang-jun  CHENG Xie-xiong
Abstract:Feature extraction is an important area of face recognition.A new face image feature extraction and recognition method-Schur Orthogonal Locality Preserving Projections(Schur-OLPP) is proposed in this paper.Schur-OLPP introduces Schur decomposition in Locality Preserving Projections(LPP) to get the orthogonal vectors and extracts discriminant features.The proposed method was tested and evaluated using the Yale face database and AR face database.Nearest neighborhood(NN) algorithm was used to construct classifiers.The experimental results show that Schur-OLPP has good performance when pose,illumination condition,face expression and time change.
Keywords:orthogonal LPP  schur decomposition  discriminant information extraction  face recognition
本文献已被 CNKI 维普 万方数据 等数据库收录!
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