This paper presents a probabilistic framework for off-line multiple object tracking. At each timestep, a small set of deterministic candidates is generated which is guaranteed to ...
Autonomous robots need to track objects. Object tracking relies on predefined robot motion and sensory models. Tracking is particularly challenging if the robots can actuate on th...
For the past few years researches have been investigating enhancing tracking performance by combining several different tracking algorithms. We propose an analytically justified, ...
We propose a new technique for fusing multiple cues to robustly segment an object from its background in video sequences that suffer from abrupt changes of both illumination and p...
Francesc Moreno-Noguer, Alberto Sanfeliu, Dimitris...
Much work has been done in the field of visual object tracking, yielding a wide range of trackers, including ones aimed for multiple objects. In many cases, there may be a couplin...