The advantage of on-line boosting is taking object tracking problem as a classi fication problem.Appropriate object feature are selected based on real time chan ges in the object.However,this method has a major drawback.Due to the presence o f occlusion situation,every transformation of object features may introduce a sm all number of error features.If it tracks the object for a long time,the accumul ation of error features will cause the tracking object with position drift.The e xperimental analysis finds that in on-line boosting method,the global delivery of selector weight leads to the drift,while the actual object occlusion only aff ects a local area,but not the entire region.For this situation,this paper propos es the combination of on-line boosting and blocking to solve this problem.Its s elector weights only change in the block,not in the global area,so it avoids err ors in the global accumulation and the generation of drift.The proposed method b y tracking a variety of object video sequences shows that even for severe occlus ion cases,it also has strong robustness as well as real-time ability,namely tra cking more than 10objects.