Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
520776 | Journal of Computational Physics | 2012 | 10 Pages |
Abstract
We present a novel approach for improving particle filters for multi-target tracking. The suggested approach is based on drift homotopy for stochastic differential equations. Drift homotopy is used to design a Markov Chain Monte Carlo step which is appended to the particle filter and aims to bring the particle filter samples closer to the observations while at the same time respecting the target dynamics. We have used the proposed approach on the problem of multi-target tracking with a nonlinear observation model. The numerical results show that the suggested approach can improve significantly the performance of a particle filter.
Related Topics
Physical Sciences and Engineering
Computer Science
Computer Science Applications
Authors
Vasileios Maroulas, Panos Stinis,