Multi-view Geometry and Deep Learning Based Drone Detection and Localization

被引：0

作者：

Shinde, Chinmay ^{[1
]}

Lima, Rolif ^{[1
]}

Das, Kaushik ^{[1
]}

机构：

[1] TCS Innovat Lab, Robot & Embedded Syst Grp, Bangalore, Karnataka, India

来源：

2019 FIFTH INDIAN CONTROL CONFERENCE (ICC) | 2019年

关键词：

MOVING OBJECT DETECTION; UAV;

D O I：

10.1109/indiancc.2019.8715593

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

A real-time vision based detection and 3D pose estimation of intruder Unmanned Aerial Vehicles (UAVs) is presented. Proposed method utilizes a cooperative team of UAVs mounted with monocular camera to detect the intruder UAV and simultaneously localize it. Detection is performed by using YOLOv2 deep learning network architecture while the position is obtained using multi-view geometry. General dynamics of the drone are considered to improve the target position estimate obtained from the image based estimate.

引用

页码：289 / 294

页数：6

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