Robust, real-time tracking of objects from visual data requires probabilistic fusion of multiple visual cues. Previous approaches have either been ad hoc or relied on a Bayesian n...
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 ...
We address the problem of automatic object classification for traffic scene surveillance, which is very challenging for the low resolution videos, large intraclass variations and ...
It was recently proposed the use of Bayesian networks for object tracking. Bayesian networks allow to model the interaction among detected trajectories, in order to obtain a relia...
Arnaldo J. Abrantes, Jorge S. Marques, Pedro Mende...
In thispaper, the problem ofsimultaneousmotionestimation of multiple independently moving objects is addressed. A novel Bayesian approach is designedfor solvingthisproblem using t...