A local hierarchical approach for background modeling and moving targets detection

Abstract

In the process of the video sequence analysis, the approach of the background modeling and moving target detection is an important problem. To get the precise contour of the targets, the Gaussian Mixture Model (GMM) is one of the models which used frequently when the background is stable. But the effect is not so ideal if we use the GMM only. A top-to-bottom Local Hierarchical GMM (LHGMM) is proposed in this paper. Firstly, the particle filter algorithm is used to track the targets, and the rough external contour can be gotten. In the area we use the block-based GMM and the pixelbased GMM to update the background and detect the moving targets. Then the detection results are fed back to the tracking frame to revise the updating area. The experiment results show that the algorithm proposed in this paper can adapt to the moving changes of the targets, and the targets can be tracked accurately.