Getting trapped in suboptimal local minima is a perennial problem in model based vision, especially in applications like monocular human body tracking where complex nonlinear para...
: This paper addresses the inference of probabilistic classification models using weakly supervised learning. The main contribution of this work is the development of learning meth...
Applications such as traffic surveillance require a real-time and accurate method for object tracking. We propose to represent scene observations with parabola segments with an alg...
Francis Deboeverie, Kristof Teelen, Peter Veelaert...
The very nature of implementing and evaluating fully distributed algorithms or protocols in application-layer overlay networks involves certain programming tasks that are at best m...
Traditional methods for creating classifiers have two main disadvantages. Firstly, it is time consuming to acquire, or manually annotate, the training collection. Secondly, the da...