Hazmat label recognition and localization for rescue robots in disaster scenarios

Publikation: Beitrag in Buch/Bericht/TagungsbandKonferenzbeitrag

1 Zitat (Scopus)

Abstract

Firefighting and rescue live victims operations are inherently dangerous, but the imminent danger of release of a hazardous substance creates an additional risk. Thus, identification of hazardous materials during robot assisted search and rescue missions can help e.g. firefighters or rescue teams to improve such rescue operations. The paper deals with the development of such a robotic machine vision system for hazmat label recognition. Classical computer vision methods but also state-of-the-art deep learning based detection algorithms were implemented and evaluated. Special focus was put on the robustness of detection and recognition with limited hardware resources and the influence of background image structures and light conditions.

OriginalspracheEnglisch
TitelIS&T Electronic Imaging 2019
Band2019
Auflage7
DOIs
PublikationsstatusVeröffentlicht - 13 Jän 2019
VeranstaltungIntelligent Robotics and Industrial Applications using Computer Vision 2019 - San Francisco, USA/Vereinigte Staaten
Dauer: 13 Jän 201917 Jän 2019
https://www.imaging.org/site/IST/Conferences/EI/EI_2019/Conference/C_IRIACV.aspx

Publikationsreihe

NameIS and T International Symposium on Electronic Imaging Science and Technology

Konferenz

KonferenzIntelligent Robotics and Industrial Applications using Computer Vision 2019
Land/GebietUSA/Vereinigte Staaten
OrtSan Francisco
Zeitraum13.01.201917.01.2019
Internetadresse

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