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...
Most work in computer vision has concentrated on studying the individual effects of motion and illumination on a 3D object. In this paper, we present a theory for combining the ef...
High dimensional data has always been a challenge for clustering algorithms because of the inherent sparsity of the points. Recent research results indicate that in high dimension...
This paper discusses techniques for visualizing structure in video data and other data sets that represent time snapshots of physical phenomena. Individual frames of a movie are t...
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...