Abstract：In this paper,a multi-region sampling object tracking algorithm based on optimization weight is proposed in order to solve the problems of regional diversity and the tracking precision decreased,object tracking instability introduced by object tracking method based on multi-region sampling.In our method,region optimization weight and improved sub-region resampling method is proposed,the regional confidence level of each sub-region is optimized by using the optimization weight to appropriate increase the number of particles low regional confidence level region acquired during resampling phase,under the premise of ensuring the particles is effective allocation according to the regional confidence level,the regional diversity decreasing phenomenon is impactful restrained.In sub-region,the particle weight optimization weight is used to optimize particle weight and set resampling threshold,so as to alleviate particle impoverishment and make full use of effective particle information.Experimental results show that the proposed method can effectively improve the object tracking accuracy and stability.
2016, Vol. 37 
