We derive a probabilistic framework for robust, realtime, visual tracking of multiple previously unseen objects from a moving camera. This framework models the discrete depth orde...
In this paper, we propose a method for monitoring the motion of cows by tracking the white patterns on them with constrained deformable models. As input for observation, we use im...
Visual tracking is still a challenging problem in computer vision. The applications of Visual Tracking are far-reaching, ranging from surveillance and monitoring to smart rooms. I...
We address the problem of multi-person dataassociation-based tracking (DAT) in semi-crowded environments from a single camera. Existing trackletassociation-based methods using pur...
Most tracking algorithms are based on the maximum a posteriori (MAP) solution of a probabilistic framework called Hidden Markov Model, where the distribution of the object state a...