Supervised locality preserving projection and tensor decomposition for multi-view face recognition
基于SLPP和张量分解相结合的人脸识别*

To solve the incapability of multi-linear analysis algorithm with multi-view face images, this paper proposed an improved algorithm . A supervised locality preserving projection that accurately described the nonlinearity in pose embedding space was introduced to project the face images into a low dimensional subspace. In the SLPP algorithm the neighboring points as supervised information could find the global structure as well as local structure. Combining with tensor decomposition and kernel methods, it well learned a set of nonlinear mapping functions from the embedding space into the input space. The proposed method was evaluated on Oriental Face database of multi-view face images in comparison to the other subspace methods. Experimental results show the effectiveness of the new method.