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.