Estimation of Wildfire Size and Location Using a Monocular Camera on a Semi-autonomous Quadcopter

Lucas Goncalves de Paula, Kristian Hyttel, Kenneth Richard Geipel, Jacobo Eduardo de Domingo Gil, Iuliu Novac, Dimitrios Chrysostomou*

*Kontaktforfatter

Publikation: Bidrag til bog/antologi/rapport/konference proceedingKonferenceartikel i proceedingForskningpeer review

1 Citationer (Scopus)
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Abstract

This paper addresses the problem of estimating the location and size of a wildfire, within the frame of a semi-autonomous recon and data analytics quadcopter. We approach this problem by developing three different algorithms, in order to accommodate this problem. Two of these taking into the account that the middle of the camera’s FOV is horizontal with respect to the drone it is mounted. The third algorithm relates to the bottom point of the FOV, directly under the drone in 3D space. The evaluation shows that having the pixels correlate to ratios in percentages rather than predetermined values, with respect to the edges of the fire, will result in better performance and higher accuracy. Placing the monocular camera horizontally in relation to the drone will provide an accuracy of 68.20%, while mounting the camera with an angle, will deliver an accuracy of 60.76%.

OriginalsprogEngelsk
TitelComputer Vision Systems : 12th International Conference, ICVS 2019, Thessaloniki, Greece, September 23–25, 2019, Proceedings
RedaktørerDimitrios Tzovaras, Dimitrios Giakoumis, Markus Vincze, Antonis Argyros
Antal sider10
ForlagSpringer
Publikationsdato1 jan. 2019
Sider133-142
ISBN (Trykt)978-3-030-34994-3
ISBN (Elektronisk)978-3-030-34995-0
DOI
StatusUdgivet - 1 jan. 2019
Begivenhed12th International Conference on Computer Vision Systems, ICVS 2019 - Thessaloniki, Grækenland
Varighed: 23 sep. 201925 sep. 2019

Konference

Konference12th International Conference on Computer Vision Systems, ICVS 2019
Land/OmrådeGrækenland
ByThessaloniki
Periode23/09/201925/09/2019
NavnLecture Notes in Computer Science
Vol/bind11754 LNCS
ISSN0302-9743

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