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基于核相关滤波的长时间目标跟踪

Long Time Target Tracking Based on Kernel Correlation Filtering

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摘要

针对传统跟踪方法在严重遮挡情况下出现目标跟踪漂移和丢失的问题, 在核相关滤波跟踪框架下提出一种长时间稳健的目标跟踪算法。在跟踪过程中引入包含遮挡信息的组合置信度测量方法, 用于稳健更新。如果核相关滤波算法中置信度的结果表明目标被遮挡, 则引入块均值漂移算法来跟踪目标。利用局部信息获取目标的最终位置。用OTB-13测试库中的8组视频序列测试算法的性能, 相比传统的核相关滤波算法, 精确度提高了0.7%, 成功率提高了5.7%。测试结果表明在目标发生严重遮挡时, 该算法仍具有较好的跟踪效果, 能实现目标长时间稳定的跟踪。

Abstract

Focusing on the target tracking drift and loss problems under severe occlusion for the traditional tracking methods, a long-term robust target tracking algorithm is proposed in the framework of Kernelized Correlation Filter (KCF) tracking. A combined confidence measurement method including occlusion information is introduced during the tracking process and used for the robust updates. If the result of the confidence graph by the KCF algorithm indicates that the target is occluded, a block mean shift (MS) algorithm is introduced to track this target and the local information is used to obtain the final location of this target. The performance of this algorithm is tested based on the eight sets of video sequences in the OTB-13 test library. The accuracy is increased by 0.7% and the success rate is increased by 5.7% compared with those of the traditional KCF algorithms. The test results show that even when the target is seriously occluded, the proposed algorithm still has a good tracking effect and a long-term stable target tracking is realized.

Newport宣传-MKS新实验室计划
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中图分类号:TP391

DOI:10.3788/lop56.021502

所属栏目:机器视觉

基金项目:国家自然科学基金(61863023)、兰州交通大学优秀科研团队项目(201701)

收稿日期:2018-06-01

修改稿日期:2018-07-05

网络出版日期:2018-08-08

作者单位    点击查看

杨剑锋:兰州交通大学自动化与电气工程学院, 甘肃 兰州 730070
张建鹏:兰州交通大学自动化与电气工程学院, 甘肃 兰州 730070

联系人作者:杨剑锋(jfyang@mail.lzjtu.cn)

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引用该论文

Yang Jianfeng,Zhang Jianpeng. Long Time Target Tracking Based on Kernel Correlation Filtering[J]. Laser & Optoelectronics Progress, 2019, 56(2): 021502

杨剑锋,张建鹏. 基于核相关滤波的长时间目标跟踪[J]. 激光与光电子学进展, 2019, 56(2): 021502

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