We propose a family of learning algorithms based on a new form of regularization that allows us to exploit the geometry of the marginal distribution. We focus on a semi-supervised...
Finding correspondences between feature points is one
of the most relevant problems in the whole set of visual
tasks. In this paper we address the problem of matching
a feature ...
We consider the problem of visual tracking of regions of interest in a sequence of motion blurred images. Traditional methods couple tracking with deblurring in order to correctly...
In this paper we present a probabilistic framework for tracking objects based on local dynamic segmentation. We view the segn to be a Markov labeling process and abstract it as a ...
In this paper, we investigate the use of discriminant techniques in the elastic graph matching (EGM) algorithm. First we use discriminant analysis in the feature vectors of the no...
Stefanos Zafeiriou, Anastasios Tefas, Ioannis Pita...