This paper presents a bottom-up tracking algorithm for surveillance applications where speed and reliability in the case of multiple matches and occlusions are major concerns. The...
Visual object tracking can be considered as a figure-ground classification task. In this paper, different features are used to generate a set of likelihood maps for each pixel i...
We describe a method for selecting optimal actions affecting the sensors in a probabilistic state estimation framework, with an application in selecting optimal zoom levels for a ...
Benjamin Deutsch, Matthias Zobel, Joachim Denzler,...
This paper addresses online learning of reference object distribution in the context of two hybrid tracking schemes that combine the mean shift with local point feature correspond...
The best of Kalman-filter-based frameworks reported in the literature for rigid object tracking work well only if the object motions are smooth (which allows for tight uncertainty ...