基于模板更新的自适应Mean-shift跟踪算法

Template Updating Based Adaptive Tracking Algorithm Using Mean-shift

提出了一种利用Mean-shift算法处理目标跟踪定位,并以SIFT特征点匹配结果的最小二乘模型来求解缩放系数和更新目标模型的自适应跟踪方法。该方法实现了目标的快速跟踪,解决了模板更新和目标的尺度缩放问题。实验结果表明,该算法在处理目标尺度变化较大的情况下具有很强的鲁棒性。

This paper proposed an adaptive tracking algorithm in which the Mean-shift algorithm is taken to obtain target position.Among this framework,the target model is updated by analyzing the results of SIFT points matching using least-squares model.This algorithm can fast track target with the advantages that the template updating and the finding of scale coefficients are implemented at the same time.The experimental results show that the algorithm is very robust to the cases that the scales of target vary largely.