基于CNN检测器的室内无人机定位技术

Вадим Горбачев, V. Gorbachev, Юрий Блохинов, Y. Blokhinov, Андрей Никитин, A. Nikitin, Екатерина Андриенко, E. Andrienko
{"title":"基于CNN检测器的室内无人机定位技术","authors":"Вадим Горбачев, V. Gorbachev, Юрий Блохинов, Y. Blokhinov, Андрей Никитин, A. Nikitin, Екатерина Андриенко, E. Andrienko","doi":"10.30987/graphicon-2019-2-280-284","DOIUrl":null,"url":null,"abstract":"The article presents the drone positioning technology in a multi-camera system by using the detection algorithm. Paper describes positioning system and algorithm for calculating 3d drone coordinates based on its image position, detected on images of stationary video cameras. Positioning enables automatically control the drone when precise data from satellite navigation systems are not available, for example, in closed hangars. The developed technology is used to create a complex of automatic visual control of aircraft. The ways of adaptation of neural network detection algorithm to the problem of drone detection are presented. The main attention is paid to the methods of training data preparation. It is shown that high accuracy can be achieved using synthesized images without any real data or manual labelling.","PeriodicalId":409819,"journal":{"name":"GraphiCon'2019 Proceedings. Volume 2","volume":"207 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Technology for Indoor Drone Positioning Based on CNN Detector\",\"authors\":\"Вадим Горбачев, V. Gorbachev, Юрий Блохинов, Y. Blokhinov, Андрей Никитин, A. Nikitin, Екатерина Андриенко, E. Andrienko\",\"doi\":\"10.30987/graphicon-2019-2-280-284\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The article presents the drone positioning technology in a multi-camera system by using the detection algorithm. Paper describes positioning system and algorithm for calculating 3d drone coordinates based on its image position, detected on images of stationary video cameras. Positioning enables automatically control the drone when precise data from satellite navigation systems are not available, for example, in closed hangars. The developed technology is used to create a complex of automatic visual control of aircraft. The ways of adaptation of neural network detection algorithm to the problem of drone detection are presented. The main attention is paid to the methods of training data preparation. It is shown that high accuracy can be achieved using synthesized images without any real data or manual labelling.\",\"PeriodicalId\":409819,\"journal\":{\"name\":\"GraphiCon'2019 Proceedings. Volume 2\",\"volume\":\"207 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-11-11\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"GraphiCon'2019 Proceedings. Volume 2\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.30987/graphicon-2019-2-280-284\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"GraphiCon'2019 Proceedings. Volume 2","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.30987/graphicon-2019-2-280-284","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

摘要

本文介绍了在多摄像头系统中利用检测算法实现无人机定位的技术。本文介绍了一种基于固定摄像机图像检测到的无人机图像位置计算无人机三维坐标的定位系统和算法。当无法获得卫星导航系统的精确数据时,例如在封闭的机库中,定位可以自动控制无人机。所开发的技术用于创建飞机自动视觉控制综合体。提出了将神经网络检测算法应用于无人机检测问题的方法。主要关注训练数据的准备方法。结果表明,在没有任何真实数据或人工标记的情况下,使用合成图像可以达到很高的精度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Technology for Indoor Drone Positioning Based on CNN Detector
The article presents the drone positioning technology in a multi-camera system by using the detection algorithm. Paper describes positioning system and algorithm for calculating 3d drone coordinates based on its image position, detected on images of stationary video cameras. Positioning enables automatically control the drone when precise data from satellite navigation systems are not available, for example, in closed hangars. The developed technology is used to create a complex of automatic visual control of aircraft. The ways of adaptation of neural network detection algorithm to the problem of drone detection are presented. The main attention is paid to the methods of training data preparation. It is shown that high accuracy can be achieved using synthesized images without any real data or manual labelling.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信