一种多目标检测跟踪算法研究
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河北省创新能力提升计划项目(19450103D)


Research on a multi-target detection and tracking algorithm
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    摘要:

    针对多目标跟踪领域中现有研究方法存在的实时性差、易漂移等问题,基于YOLOv3算法和KCF算法,提出了一种多目标检测跟踪算法。首先,利用训练好的YOLOv3网络获取视频中目标的位置,并对各个目标进行ID分配;其次,将多个目标并行输入到基于核相关滤波的跟踪模块进行目标跟踪;然后,判断是否满足启动修正策略的条件,若满足则用检测模块的结果去修正跟踪模块的结果;最后,利用跟踪结果更新核相关滤波器模型。实验结果表明,将算法应用于OTB2015数据集中的4组含有多种干扰的视频序列,其跟踪精确度达82.4%,跟踪成功率达81.1%,能够满足跟踪实时性要求。因此,所提算法不但有效,且具有更强的鲁棒性,为多目标跟踪领域提供了新的研究思路。

    Abstract:

    Aiming at the problems of poor real-time performance and easy drift in the existing research methods in the field of multi-target tracking,a multi-target detection and tracking algorithm was proposed based on YOLOv3 algorithm and KCF algorithm.Firstly,the trained YOLOv3 network was used to obtain the location of the target in the video,and the ID of each target was allocated;Secondly,multiple targets were input into the tracking module based on kernel correlation filter in parallel for target tracking;Then,the conditions for starting the correction strategy were judged,if they were met,the results of the detection module were used to correct the results of the tracking module;Finally,the kernel correlation filter model was updated by using the tracking results.The experimental results show that when the algorithm is applied to four groups of video sequences containing multiple interferences in OTB2015 data set,the tracking accuracy reaches 82.4%,the tracking success rate reaches 81.1%,and meets the requirements of real-time tracking.Therefore,the algorithm is not only valid,but also has stronger robustness to provide a new research method for the field of multi-target tracking.

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杨文焕,翟 雨,殷亚萍,王晓君.一种多目标检测跟踪算法研究[J].河北科技大学学报,2022,43(2):127-136

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  • 收稿日期:2021-04-21
  • 最后修改日期:2021-10-04
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  • 在线发布日期: 2022-05-03
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