Fusion of Uncorrelated Discriminant Vectors, Correlated Discriminant Vectors and Kernelized Discriminant Vectors

摘要

In this paper we obtain higher pattern analysis accuracy through the fusion of uncorrelated discriminant vectors, correlated discriminant vectors and kernelized discriminant vectors by some fusion theory and technology which is carried out by some estimation method of multi-feature. Based on some different features such as linear and non-linear features, correlated and uncorrelated features, one estimation method of multi-feature is proposed to fuse these different vectors. Finally experiments on human face recognition are carried out and prove our methods to be available.