In recent years, sparse representation originating from signal compressed sensing theory has attracted increasing interest in computer vision research community. However, to our b...
A collaborative framework for detecting the different sources in mixed signals is presented in this paper. The approach is based on CHiLasso, a convex collaborative hierarchical s...
Abstract. By coding the input testing image as a sparse linear combination of the training samples via l1-norm minimization, sparse representation based classification (SRC) has b...
We address the problem of computing joint sparse representation of visual signal across multiple kernel-based representations. Such a problem arises naturally in supervised visual...
Particle filters (PFs) are Bayesian filters capable of modeling nonlinear, non-Gaussian, and nonstationary dynamical systems. Recent research in PFs has investigated ways to approp...