A Reversible and Stable Orthogonal Tensor Projection Method in Subspace Learning
Zhaoxiong Zeng, Lei Huang, Changping Liu · 2009
In this paper we proposed a MFA based RSOTP subspace learning method. By employing stable discriminant vector in initialization and using an alternative orthogonal selection and throwing off weight matrix, this approach enhances the robustness of the learning process and strengthens the classification ability, and achieves better recognition performance on both large and small face datasets than conventional techniques.