Abstract： Proposed in this paper is a human object tracking algorithm for HRI (Humanrobot interaction) as a solution to the interference by similar human objects when a robot is tracking a specified human object. In the proposed algorithm, all interference regions are regarded as candidate targets, and a particle distribution model based on overlapping rate is established to make particles converge to all candidate targets via a mean shift with a reduced number. Then, by taking the total error of weight distance and the target size as the clustering conditions, particles are divided into corresponding candidate target particles, and the best candidate target is selected as the tracking result. The experimental results show that the proposed algorithm can track targets accurately in the presence of surrounding similar objects, and  it possesses strong robustness and good realtime performance.