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...
Subspace learning approaches have attracted much attention in academia recently. However, the classical batch algorithms no longer satisfy the applications on streaming data or la...
Jun Yan, Benyu Zhang, Shuicheng Yan, Qiang Yang, H...
Three methods for the efficient downdating, composition and splitting of low rank singular value decompositions are proposed. They are formulated in a closed form, considering the ...
Modeling subspaces of a distribution of interest in high dimensional spaces is a challenging problem in pattern analysis. In this paper, we present a novel framework for pose inva...
This paper investigates the use of range images of faces for recognizing people. 3D scans of faces lead to range images that are linearly projected to low-dimensional subspaces fo...