基于最近正交矩阵的二维鉴别投影及人脸识别应用

Two Dimensional Discriminative Projection Based on Nearest Orthogonal Matrix and its Application to Face Recognition

为了解决人脸识别中的光照干扰问题,提出基于最近正交矩阵的二维鉴别投影方法.首先利用奇异值分解获取人脸图像矩阵的最近正交矩阵表示;然后利用获得的最近正交矩阵分别构建基于最近正交矩阵的类内散度和基于最近正交矩阵的类间散度;最后通过最大化类间散度同时最小化类内散度获取二维鉴别投影,并通过该投影获得低维特征.在Yale,CMU-PIE以及AR数据库上进行人脸识别实验,证明了该方法的有效性.

To solve the interferential problem of illumination in face recognition,this paper proposes a methodcalled two dimensional discriminative projection based on nearest orthogonal matrix(2DDP-NOM).Itobtains nearest orthogonal matrix representation of face image matrix by singular value decompositionfirstly;then constructs the intra-class scatter based on nearest orthogonal matrix and the inter-class scatterbased on nearest orthogonal matrix by nearest orthogonal matrix;lastly,obtains two dimensional discriminativeprojection by maximizing the inter-class scatter and minimizing the intra-class scatter simultaneouslyand gets the low dimensional features by this projection.Experiments are performed on Yale,CMU-PIE andAR databases and the experimental results demonstrate the effectiveness of2DDP-NOM.