A Novel Approach for Face Recognition Based on Supervised Locality Preserving Projection and Maximum Margin Criterion

In this paper, we propose a novel approach for face recognition, that combine Supervised Locality Preserving Projection (SLPP) with Maximum Margin Criterion (MMC) for preserving the within-class neighborhood structure of facial manifold and meanwhile finding an optimal feature space for classification. We also give an effective solution to the eigenvalue problem. Our method can avoid the preprocessing stage of resizing the original image resolution and Principle Component Analysis (PCA) projection, so there is no information lost. Experiment results demonstrate the effectiveness of the proposed approach on the ORL face database.