The work presented in this paper explores a supervised method for learning a probabilistic model of a lexicon of VerbNet classes. We intend for the probabilistic model to provide ...
Modeling subspaces of a distribution of interest in high dimensional spaces is a challenging problem in pattern analysis. In this paper, we present a novel framework for pose inva...
We propose the use of latent space models applied to local invariant features for object classification. We investigate whether using latent space models enables to learn patterns...
Florent Monay, Pedro Quelhas, Daniel Gatica-Perez,...
Image categorization involves the well known difficulties with different visual appearances of a single object, but introduces also the problem of within-category variation. This ...
Triangle strips have been widely used for static mesh representation because they are optimal for rendering. This primitive reduces the number of vertices sent to the graphics pip...
J. Francisco Ramos, Miguel Chover, Oscar Belmonte,...