This paper 1 addresses the problem of efficient visual 2D template tracking in image sequences. We adopt a discriminative approach in which the observations at each frame yield di...
Matching articulated shapes represented by voxel-sets reduces to maximal sub-graph isomorphism when each set is described by a weighted graph. Spectral graph theory can be used to...
Diana Mateus, Radu Horaud, David Knossow, Fabio Cu...
In this paper, we formulate the shape localization problem in the Bayesian framework. In the learning stage, we propose the Constrained RankBoost approach to model the likelihood ...
A linear, discriminative, supervised technique for reducing feature vectors extracted from image data to a lower-dimensional representation is proposed. It is derived from classica...
We consider the problem of tracking a given set of point features over large sequences of image frames. A classic procedure for monitoring the tracking quality consists in requirin...