Research on Object Tracking Technology Based on Region Proposal Siamese Network

Zhe Gu, Yanjing Lei, Di Cao, Lue Zhan
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Abstract

Most of the existing trackers have high performance and good effect, but it is difficult to have fast speed and can not meet the real-time requirements. Therefore, the development of target tracking system with high accuracy and good robustness has become an urgent task for researchers. This paper proposes to add an Region Proposal Network (RPN) module based on the structure of the traditional Siamese Network (SiamFC), calculate the template and branch of the Siamese sub network in advance in the reasoning stage, and decompose the tracking task into task nodes that are detected first and then matched for real-time online tracking. The experimental results on VOT2015, VOT2018 and OTB2015 data sets show that compared with other trackers, the model based on SiamRPN proposed in this paper shows better performance in achieving the dual goals of high accuracy and low robustness.
基于区域提议暹罗网络的目标跟踪技术研究
现有的大多数跟踪器性能高,效果好,但速度快,不能满足实时性要求。因此,开发高精度、鲁棒性好的目标跟踪系统已成为研究人员迫切需要解决的问题。本文提出在传统连体网络(SiamFC)结构的基础上增加区域建议网络(RPN)模块,在推理阶段提前计算连体子网络的模板和分支,并将跟踪任务分解为先检测后匹配的任务节点进行实时在线跟踪。在VOT2015、VOT2018和OTB2015数据集上的实验结果表明,与其他跟踪器相比,本文提出的基于SiamRPN的模型在实现高精度和低鲁棒性的双重目标方面表现出更好的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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