Abstract. In this paper, we propose a particle filtering approach for tracking applications in image sequences. The system we propose combines a measurement equation and a dynamic ...
The recent development of Sequential Monte Carlo methods (also called particle filters) has enabled the definition of efficient algorithms for tracking applications in image sequen...
We present a multi modal sequential importance resampling particle filter algorithm for object tracking. We consider a hidden state sequence linked to several observation sequence...
Sequential importance sampling (SIS), also known as particle filtering, has drawn increasing attention recently due to its superior performance in nonlinear and non-Gaussian dynam...
Yan Zhai, Mark B. Yeary, Joseph P. Havlicek, Jean-...
We present a generative model and stochastic filtering algorithm for simultaneous tracking of 3D position and orientation, non-rigid motion, object texture, and background texture...
Tim K. Marks, John R. Hershey, J. Cooper Roddey, J...