基于核的正交局部保持投影的人脸识别

针对发掘人脸图像中的高维非线性结构，本文将加核及向量间相互正交两种思想同时引入局部保留投影算法中，提出了一种新的基于核的正交局部保持投影(Kernel based Orthogonal Locality Preserving Projections, KOLPP)的非线性子空间人脸识别算法并给出了其推导过程。该算法首先利用核的方法提取人脸图像中的非线性信息，并将其投影在一个高维非线性空间，在保证各向量正交的同时，通过局部保持投影算法做一线性映射，从而更好地提取人脸非线性局部邻域结构特征。在ORL和Yale人脸库上的试验证明了该文所提算法的有效性。

Kernel Based Orthogonal Locality Preserving Projections for Face Recognition

In this paper, considering kernel and orthogonal basis functions, a new method named kernel based orthogonal locality preserving projections algorithm, which aims at discovering an embedding that preserves nonlinear information is proposed for face representation and recognition. In this algorithm, first, the nonlinear kernel mapping is used to map the face data into an implicit feature space, and then a linear transformation which produces orthogonal basis functions is performed to preserve locality geometric structures of the face image. Experiments based on both ORL and Yale face database demonstrate the effectiveness of the new algorithm.