Face recognition based on kernel orthogonal local discriminant embedding

In view of the problems of nonlinear feature extraction in face recognition, an algorithm based on kernel orthogonal local discriminant embedding(KOLDE) for face recognition is proposed in this paper. Firstly, the proposed algorithm gets orthogonal local discriminant embedding(OLDE) algorithm by introducing the orthogonal constraint of basis vectors. Then the OLDE algorithm is expanded to high dimensional feature space by nonlinear mapping in order to deal with dataset of highly nonlinear structure. Finally, the kernel orthogonal local discriminant embedding algorithm is obtained by introducing the orthogonal constraint of basis vectors and traditional LDE method in kernel space. The experimental results on ORL and PIE face database illustrate the effectiveness of the proposed method.