A natural representation of data is given by the parameters which generated the data. If the space of parameters is continuous, then we can regard it as a manifold. In practice, w...
In this paper, we present a novel maximum correlation sample subspace method and apply it to human face detection [1] in still images. The algorithm starts by projecting all the t...
Bayesian subspace analysis has been successfully applied in face recognition. However, it suffers from its operating on a whole face difference and using one global linear subspac...
We propose a sinogram restoration method which consists of a patch-wise non-linear processing, based on a sparsity prior in terms of a learned dictionary. An off-line learning pro...
We present a theory for constructing linear subspace approximations to face-recognition algorithms and empirically demonstrate that a surprisingly diverse set of face-recognition a...