%0 Journal Article
%T Applying Dynamic Model for Multiple Manoeuvring Target Tracking Using Particle Filtering
%A Mohammad Javad Parseh
%A Saeid Pashazadeh
%J Computer Science
%D 2012
%I arXiv
%R 10.5121/ijitca.2012.2404
%X In this paper, we applied a dynamic model for manoeuvring targets in SIR particle filter algorithm for improving tracking accuracy of multiple manoeuvring targets. In our proposed approach, a color distribution model is used to detect changes of target's model . Our proposed approach controls deformation of target's model. If deformation of target's model is larger than a predetermined threshold, then the model will be updated. Global Nearest Neighbor (GNN) algorithm is used as data association algorithm. We named our proposed method as Deformation Detection Particle Filter (DDPF) . DDPF approach is compared with basic SIR-PF algorithm on real airshow videos. Comparisons results show that, the basic SIR-PF algorithm is not able to track the manoeuvring targets when the rotation or scaling is occurred in target' s model. However, DDPF approach updates target's model when the rotation or scaling is occurred. Thus, the proposed approach is able to track the manoeuvring targets more efficiently and accurately.
%U http://arxiv.org/abs/1211.4524v1