We consider a class of learning problems that involve a structured sparsityinducing norm defined as the sum of -norms over groups of variables. Whereas a lot of effort has been pu...
The linear model with sparsity-favouring prior on the coefficients has important applications in many different domains. In machine learning, most methods to date search for maxim...
We present in this paper a novel approach for shape description based on kernel principal component analysis (KPCA). The strength of this method resides in the similarity (rotatio...
— Today, there are many opportunities to create vision-based intelligent systems that are human-centric. This is a very rich area because humans are very complex, and the number ...
Robert Bodor, Andrew Drenner, Paul R. Schrater, Ni...
We propose a marker-less model-based camera tracking approach, which makes use of GPU-assisted analysis-by-synthesis methods on a very wide field of view (e.g. fish-eye) camera. ...