基于遮挡检测的核相关滤波目标跟踪算法

Survey on the Statistic Method Based on Video

针对核相关滤波目标跟踪算法在目标跟踪中存在严重遮挡的问题,本文提出了基于遮挡检测的核相关滤波目标跟踪算法。该算法首先在目标跟踪时利用峰值旁瓣比进行遮挡检测判断,然后当目标未遮挡时,继续使用核相关滤波模块进行跟踪,当有遮挡时,在目标出遮挡之后使用本文所提出的分类器进行目标再检测。为了验证本文的有效性,采用OTB-2013中21组遮挡数据集,并和OTB-2013中跟踪性能较好的跟踪算法进行对比,实验表明本文算法能有效的解决在目标跟踪中存在的严重遮挡的问题。

AS Kernelized Correlation Filters(KCF)tracking algorithm has poor in handling heavy occlusion,this paper propose a Target Tracking based on Occlusion Detection and Kernelized Correlation Filters.Firstly used the peak sidelobe ratio to detect the occlusion when the target is tracked.Then when the target is not occluded,it continues to use the kernel-based filtering module to track it.When the occlusion occurs,we do the re-detection which used the classifier.In order to verify the validity of this paper,we use 21 groups of occlusion datasets in OTB-2013 and compare with the tracking algorithm with good tracking performance in OTB-2013.Experimental results show that the proposed algorithm can effectively solve the problem of severe occlusion of targets.