  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.
