In this paper, we present a probabilistic framework for automatic detection and tracking of objects. We address the data association problem by formulating the visual tracking as ...
We propose a framework for general multiple target tracking, where the input is a set of candidate regions in each frame, as obtained from a state of the art background learning, ...
Abstract. We describe a Markov chain Monte Carlo based particle filter that effectively deals with interacting targets, i.e., targets that are influenced by the proximity and/or be...
In many multitarget tracking applications in computer vision, a detection algorithm provides locations of potential targets. Subsequently, the measurements are associated with pre...
With the wide application of green fluorescent protein (GFP) in the study of live cells, there is a surging need for the computer-aided analysis on the huge amount of image seque...