在基于模式匹配的目标跟踪算法中，由于受遮挡、自身外观变化的影响，模板更新问题一直是目标跟踪的一个难题，因为遮挡和外观变化均表现为目标内灰度的变化，但由障碍物遮挡引起的灰度变化不能更新为模板；而由目标自身引起的灰度变化又要即时地更新为模板。为此，提出一种带有遮挡和外观变化判断的局部模板更新算法。算法使用分块模板并根据目标中变化的信息分别来自目标和背景的概率来区别外观变化和遮挡这两种情况。目标被部分遮挡时，通过不更新模板来防止障碍物信息混入模板；目标外观变化时，提出一种新的局部模板更新算法以适应目标的不断变化。实验结果表明，该算法既能较好地适应目标的外观变化，又具有较强的抗遮挡能力，比整体模板更新算法具有更好的鲁棒性。

Influenced by appearance changes and occlusions, template updating has been one of the most difficult problems in the object tracking algorithms based on pattern matching. Because both appearance changes and occlusions can lead to the changes in the intensity of object, however, changes that result from the obstacles can’t be updated as the template; while changes that result from the object in itself should be updated in time. Therefore, a local template update method with the discrimination between occlusions and appearance changes is presented in this paper. The proposed method uses the fragment template for the tracking and distinguishes occlusions from appearance changes according to the probabilities of which varied gray level information belongs to the target and to the background region. The template is preserved to prevent the information of the obstacles from contaminating the template when the target has been partially occluded; while a new adaptive local template update algorithm is used in the case of appearance changes. Experimental results are presented to demonstrate that our algorithm can be adaptive to the appearance changes as well as occlusions and is more robust than the total model update strategy.