The Research of Mean-Shift UAV Tracking Algorithm by TWH and FB-Error Restriction

Yibo Li, Qi Zhang, Senyue Zhang
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引用次数: 3

Abstract

In view of the phenomenon that the factors of occluded target and it's changed background lead to failure in the process of tracking, a MTF (Mean-shift by TWH and FBerror) tracking algorithm is proposed. Firstly, TargetWeighted Histogram (TWH) is introduced to describe target in Mean-shift tracking framework, i.e., using local-background of target to weaken inner-background features of all-region in order to make target features prominent in tracking process, secondly, FB-error restriction is introduced, the predicted results of target current position and the calculated results of mean-shift vector are combined together to estimate the final target location of time t by using weighted function about FBerror. The experimental results show that the proposed tracking algorithm has great breakthrough on tracking accuracy.
基于TWH和fb误差约束的均值漂移无人机跟踪算法研究
针对目标被遮挡和背景变化等因素导致跟踪失败的现象,提出了一种MTF (Mean-shift by TWH and FBerror)跟踪算法。首先,在Mean-shift跟踪框架中引入目标加权直方图(TWH)来描述目标,即利用目标的局部背景来减弱全区域的内背景特征,使目标特征在跟踪过程中突出;将目标当前位置的预测结果和mean-shift向量的计算结果结合起来,利用FBerror加权函数估计t时刻的最终目标位置。实验结果表明,所提出的跟踪算法在跟踪精度上有很大的突破。
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