系统工程与电子技术 ›› 2022, Vol. 44 ›› Issue (2): 401-409.doi: 10.12305/j.issn.1001-506X.2022.02.06

• 电子技术 • 上一篇    下一篇

基于无锚框的红外多类别多目标实时跟踪网络

宋子壮*, 杨嘉伟, 张东方, 王诗强, 张硕   

  1. 北京遥感设备研究所, 北京 100854
  • 收稿日期:2021-04-01 出版日期:2022-02-18 发布日期:2022-02-24
  • 通讯作者: 宋子壮
  • 作者简介:宋子壮(1995—), 男, 博士研究生, 主要研究方向为深度学习与红外目标跟踪|杨嘉伟(1963—), 男, 研究员, 博士研究生导师, 博士, 主要研究方向为空间信息传输与信息处理|张东方(1986—), 男, 高级工程师, 硕士, 主要研究方向为深度学习与智能系统设计|王诗强(1988—), 男, 工程师, 博士, 主要研究方向为机器视觉与多传感器信息融合|张硕(1994—), 男, 助理工程师, 硕士, 主要研究方向为先进红外成像技术与红外系统设计

Real-time infrared multi-class multi-target anchor-free tracking network

Zizhuang SONG*, Jiawei YANG, Dongfang ZHANG, Shiqiang WANG, Shuo ZHANG   

  1. Beijing Institute of Remote Sensing Equipment, Beijing 100854, China
  • Received:2021-04-01 Online:2022-02-18 Published:2022-02-24
  • Contact: Zizhuang SONG

摘要:

本文提出一种改进的红外多类别多目标实时跟踪网络, 在确保跟踪精度的同时, 重新设计无锚框网络结构, 进一步降低网络的参数量与推理时间。通过优化目标特征向量, 进一步提高识别精度, 同时简化与改进跟踪流程。此外, 通过细化分析相关流程执行时间, 选用GPU与CPU分别执行最优运算, 提升跟踪整体运行速度。上述方法被应用于低空海面红外目标跟踪数据集中。结果表明, 在本文所提的综合评价指标下, 所设计的网络相较其他轻量级网络评分提高1.78, 且运行速度在NVIDIA Jetson Xavier NX中达到52.37 FPS, 满足边缘端实时运行需求。

关键词: 多目标跟踪, 无锚框, 红外目标, 多类别, 边缘端实时, 重识别

Abstract:

In this paper, an improved real-time infrared multi-class multi-target tracking network is proposed, which not only ensures the tracking accuracy, but also redesigns the anchor-free network structure to further reduce the number of network parameters and the network inference latency. By optimizing the target feature vector, the recognition accuracy is further improved, and the tracking process is simplified and developed. In addition, through detailed analysis of the execution time of related processes, GPU and CPU are selected to perform the optimal operation respectively to improve the overall tracking speed. The above method is applied to the low altitude sea surface infrared target tracking dataset. The results show that under the comprehensive evaluation metric proposed in this paper, the score is increased by 1.78 and the running speed of the algorithm reaches 52.37 FPS in NVIDIA Jetson Xavier NX compared with other lightweight network, which meets the real-time operation requirements of edge devices.

Key words: multi-target tracking, anchor-free, infrared target, multi-class, real time in edge devices, re-identification

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