电子测试2024,Issue(1) :101-104.

基于跟踪检测多目标的无人机软件开发与算法分析

Development and algorithm analysis of unmanned aerial vehicle software based on tracking and detecting multiple targets

李瑞 郭斌 焦义贵
电子测试2024,Issue(1) :101-104.

基于跟踪检测多目标的无人机软件开发与算法分析

Development and algorithm analysis of unmanned aerial vehicle software based on tracking and detecting multiple targets

李瑞 1郭斌 1焦义贵1
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作者信息

  • 1. 南京多基观测技术研究院有限公司 南京 211500
  • 折叠

摘要

当前无人机多目标跟踪检测中还存在较多问题,比如精确度低以及占用内存大的问题.基于YOLOv5算法和DeepSort算法开发无人机软件,设计跟踪模板更新策略,通过检测模块将目标置信度、置信度等相关信息传输到跟踪模块实现跟踪.在YOLOv5 算法和DeepSort算法的应用下,实现对目标估计的预测和分配预测结果,确保无人机跟踪效果和速度.实验结果发现,基于YOLOv5算法和DeepSort算法的无人机软件在多目标跟踪中,可以将跟踪精度提升22%,效果显著.

Abstract

There are still many problems in the current multi target tracking and detection of unmanned aerial vehicles,such as low accuracy and large memory usage.Based on this,the YOLOv5 algorithm and DeepSort algorithm are used to complete the development of unmanned aerial vehicle software,and a tracking template update strategy is designed.Through the detection module,relevant information such as target confidence and confidence are transmitted to the tracking module to implement tracking.Under the application of YOLOv5 algorithm and DeepSort algorithm,the prediction of target estimation can be achieved,and the prediction results can be allocated to ensure the tracking effect and speed of unmanned aerial vehicles.The final experimental results found that the drone software based on YOLOv5 algorithm and DeepSort algorithm can improve tracking accuracy by 22%in multi target tracking,with significant results.

关键词

跟踪检测/多目标/无人机软件开发/算法

Key words

tracking and detection/multiple objectives/drone software development/algorithm

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出版年

2024
电子测试
北京自动测试技术研究所

电子测试

影响因子:0.332
ISSN:1000-8519
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