We address the problem of denoising for image patches. The approach taken is based on Bayesian modeling of sparse representations, which takes into account dependencies between th...
This paper analyzes the performance of the simple thresholding algorithm for sparse signal representations. In particular, in order to be more realistic we introduce a new probabi...
This paper presents a novel framework for recognition of facial action unit (AU) combinations by viewing the classification as a sparse representation problem. Based on this framew...
Mohammad H. Mahoor, Mu Zhou, Kevin L. Veon, Seyed ...
Video error concealment is a post-processing technique that conceals the errors in a decoded video sequence based on data available only at the decoder. Most of the current techni...
Assuming that a set of source signals is sparsely representable in a given dictionary, we show how their sparse recovery fails whenever we can only measure a convolved observation...