Online learning has shown to be successful in tracking of previously unknown objects. However, most approaches are limited to a bounding-box representation with fixed aspect rati...
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...
This paper presents methods for tracking moving objects in an outdoor environment. A robust tracking is achieved using feature fusion and multiple cameras. The proposed method int...
In this paper, we present a new multiple hypotheses tracking (MHT) approach. Our tracking method is suitable for online applications, because it labels objects at every frame and ...
This paper presents a robust shape-based on-line tracker for simultaneously tracking the motion of both hands, that is robust to cases of background clutter, other moving objects,...