Abstract. We present an approach to non-rigid object tracking designed to handle textured objects in crowded scenes captured by non-static cameras. For this purpose, groups of low-...
—In kernel based regression techniques (such as Support Vector Machines or Least Squares Support Vector Machines) it is hard to analyze the influence of perturbed inputs on the ...
We develop an optical flow estimation framework that focuses on motion estimation over time formulated in a Dynamic Bayesian Network. It realizes a spatiotemporal integration of ...
Volker Willert, Marc Toussaint, Julian Eggert, Edg...
The paper describes a simple but effective framework for visual object tracking in video sequences. The main contribution of this work lies in the introduction of a case-based rea...
This paper presents a new semi-competitive learning paradigm named Competitive and Cooperative Learning (CCL), in which seed points not only compete each other for updating to ada...