We propose to detect abnormal events via a sparse reconstruction over the normal bases. Given an over-complete normal basis set (e.g., an image sequence or a collection of local s...
The sparse grid discretization technique enables a compressed representation of higher-dimensional functions. In its original form, it relies heavily on recursion and complex data...
Alin Florindor Murarasu, Josef Weidendorfer, Gerri...
We propose a variant of Orthogonal Matching Pursuit (OMP), called LoCOMP, for scalable sparse signal approximation. The algorithm is designed for shift-invariant signal dictionari...
We introduce a new exemplar-based inpainting algorithm that represents the region to be inpainted as a sparse linear combination of example blocks, extracted from the image being ...
We propose a sparse non-negative image coding based on simulated annealing and matrix pseudo-inversion. We show that sparsity and non-negativity are both important to obtain part-...