Multiple information projection based on Locality Preserving Projections

With the purpose of solving feature extraction problem in face recognition area, a new manifold learning algorithm is proposed, called Multiple Locality Preserving Projections (MLPP) based on Locality Preserving Projections. The algorithm uses to select different measure matrix and constraints matrix those include intra-class matrix and inter-class matrix. The problem can be converted into the normal eigenvalue problem. When constructing the graph, this algorithm makes point with the same attributes as neighborhood points, which makes the intra-class construct save to feature space. As a result, the local construct remains stable, and at the same time the global construct tends to maximalism, so the cluster with high efficiency has been obtained. The results of the experiments on JAFFE and AT&T face database indicate that MLPP improves recognition rate.