Development of Multi-target Tracking Technique Based on Background Modeling and Particle Filtering

Based on implementing target tracking by means of particle filtering, a technique framework of tracking target by integrating particle filtering and background modeling is presented. The multi-target tracking (MTT) is classified into 5 modules as background modeling, multi-target tracking, initializing, re-initializing and particle filtering. Firstly, the author models each pixel of the image with Gaussian Mixture Model (GMM) to calculate the probability of background pixel in the current image so as to abstract foreground moving objects. Based on the background modeling, the algorithm flow and technique framework of generating the particle set of each object and particle filtering are presented. In the process of evaluating particle weight, in order to distinguish the different color features of the objects, the original algorithm (evaluating through Bhattacharyya distance) is improved. Only the color distribution of the foreground pixel in particle area after the background modeling is counted, therefore the accuracy and efficiency of target tracking are increased. The experiments prove that this algorithm can realize the effective tracking several moving persons