Researches on Scale Adaptation Strategy in Mean Shift Tracking Algorithm

The standard Mean Shift tracking algorithm is lack of scale adaptation mechanism.A familiar scale adaptation strategy is to determine the scale in current frame by running the standard Mean Shift tracking algorithm three times respectively based on the previous scale,its 10% up and 10% off scales.In this paper,the algorithm was tested on numerous typical scenes and its two drawbacks are found:(1) sometimes it may be stuck in the scale smaller than the real scale;(2) it often responds poorly to rapid scale changes.Such drawbacks can introduce additional scale error and thus increase the risk of missin tracking.Through analyzing above drawbacks in detail,we propose the revised scale adaptation algorithm,in which the criterion of optimal bandwidth selection is modified and adaptive filtering parameter is introduced.Experiment results in numerous scenes show the effectiveness and efficiency of the improved algorithm.