王慧敏.一种新的多装甲目标在线跟踪方法[J].光电子激光,2023,34(11):1178~1186
一种新的多装甲目标在线跟踪方法
A new method for online tracking of multi-armored targets
投稿时间:2022-07-04  修订日期:2022-10-08
DOI:
中文关键词:  多装甲目标  在线跟踪  视觉注意力  Gabor  卷积神经网络
英文关键词:multi-amored targets  online tracking  visual-attention  Gabor filter  convolutional neural network
基金项目:
作者单位
王慧敏 (陆军装甲兵学院 兵器与控制系北京 100072) 
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中文摘要:
      实现多装甲目标跟踪在协同跟踪和打击中发挥着至关重要的作用,而实现多装甲目标跟踪需要解决目标之间遮挡、轨迹交叉以及目标尺度不断变化等问题。因此,提出了一种基于视觉注意力的Gabor在线多装甲目标跟踪方法,实现对地面战场中多装甲目标的跟踪。通过模拟视网膜结构,构造了一种能够增强检测的视觉注意力Gabor分支,并引入时间信息,采用在线学习的目标特性卷积神经网络解决目标遮挡的问题,更重要的是,通过实际拍摄和互联网下载等手段构建了多装甲目标跟踪数据集,并且通过对目前成熟的多目标跟踪方法和本文提出的方法进行对比实验。实验证明了本文提出的方法不仅具有优异的跟踪性能,而且能够满足实际的应用需求。
英文摘要:
      The realization of multi-armored target tracking plays a vital role in cooperative tracking and strike,and the realization of multi-armored target tracking needs to solve the problems of occlusion,interspersed and constantly changing target scales between targets.Therefore,an online multi-armored target tracking method based on visual-attention Gabor filter is proposed to achieve the tracking of multi-armored targets in the ground battlefield.A visual-attention Gabor filter branch is constructed to enhance detection by simulating the retinal structure.By introducing temporal information,the problem of target occlusion is solved by using an online learned target-specific convolutional neural network.What is more important,a multi-armored target tracking dataset is constructed by means of actual shooting and downloading from the internet,and the current mature multi-target tracking methods are compared with the method proposed in this paper through experiment.The experiments show that the method in this paper not only has excellent tracking performance,but also can meet the actual application requirements.
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