Human faces manifest distinct structures and characteristics when observed in different scales. Traditional face recognition techniques mainly rely on low-resolution face images, ...
Traditional face superresolution methods treat face images as 1D vectors and apply PCA on the set of these 1D vectors to learn the face subspace. Zhang et al [7] proposed Two-dire...
Previous works have demonstrated that the face recognition performance can be improved significantly in low dimensional linear subspaces. Conventionally, principal component analy...
Image communication is a significant research area which involves improvement in image coding and communication techniques. In this paper, Principal Component Analysis (PCA) is use...
We discuss a new multi-view face recognition method that extends a recently proposed nonlinear tensor decomposition technique. We use this technique to provide a generative face m...