We consider the problem of reconstructing time sequences of spatially sparse signals (with unknown and time-varying sparsity patterns) from a limited number of linear "incohe...
In this paper, We propose an efficient compression method to encode the geometry of 3D mesh sequences of objects sharing the same connectivity. Our approach is based on the cluste...
Embedding images into a low dimensional space has a wide range of applications: visualization, clustering, and pre-processing for supervised learning. Traditional dimension reduct...
A recent trend in exemplar based unsupervised learning is to formulate the learning problem as a convex optimization problem. Convexity is achieved by restricting the set of possi...
This paper presents an approach on high-level feature detection within video documents, using a Region Thesaurus. A video shot is represented by a single keyframe and MPEG-7 featur...
Evaggelos Spyrou, Giorgos Tolias, Yannis S. Avrith...