Real-time high-resolution omnidirectional imaging platform for drone detection and tracking

被引:0
|
作者
Bilal Demir
Selman Ergunay
Gokcen Nurlu
Vladan Popovic
Beat Ott
Peter Wellig
Jean-Philippe Thiran
Yusuf Leblebici
机构
[1] École Polytechnique Fédérale de Lausanne (EPFL),
[2] Bloomberg LP,undefined
[3] Intel Corp,undefined
[4] Armasuisse Science and Technology,undefined
来源
Journal of Real-Time Image Processing | 2020年 / 17卷
关键词
Panorama; Background subtraction; High resolution; Moving object detection; Embedded system;
D O I
暂无
中图分类号
学科分类号
摘要
Drones have become steadily affordable, which raises privacy and security concerns as well as interest in drone detection systems. On the other hand, drone detection is a challenging task due to small dimensions of drones, difficulty of long-distance detection, strict real-time constraints and necessity of wide angle coverage for drones. Although different radar and audio-assisted drone detection systems have been presented, they suffer from the cost, range, or interference problems. On the contrary, a long-range detection can be obtained by a vision-based system. Aiming that, we propose a real-time moving object detection and tracking system optimized for drone detection using 16 cameras with 20 MP resolution. The proposed system detects drones from short range and long range with 360∘\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$^{\circ }$$\end{document} surveillance coverage owing high-performance ultra-high-resolution (320 MP) video-processing capability. It is able to detect drones with 100 cm diameter from 700 m distance despite deceptive background. It is interference free, so multiple systems can properly operate in the vicinity without effecting each other. It integrates processing power of embedded systems with flexibility of software to generate a full platform for drone detection and tracking.
引用
收藏
页码:1625 / 1635
页数:10
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