Infrared object tracking based on particle filter

Abstract

A novel infrared moving object tracking method based on particle filter and mean shift algorithm is presented in this paper. Based on the framework of particle filter, the mean shift algorithm is introduced as better proposal distribution to improve the sampling efficiency. Compared to conventional particle filter, the proposed method uses much fewer particles to maintain the multi-mode distribution, and overcomes the degeneration problem effectively. Experimental results on sequential images show that our method can track steadily when the object move fast or be occluded, the overall performance of the proposed method is better than traditional particle filter algorithm.