Hazmat label recognition and localization for rescue robots in disaster scenarios

Research output: Chapter in Book/Report/Conference proceedingsConference contribution

1 Citation (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.

Original languageEnglish
Title of host publicationIS&T Electronic Imaging 2019
Volume2019
Edition7
DOIs
Publication statusPublished - 13 Jan 2019
EventIntelligent Robotics and Industrial Applications using Computer Vision 2019 - San Francisco, United States
Duration: 13 Jan 201917 Jan 2019
https://www.imaging.org/site/IST/Conferences/EI/EI_2019/Conference/C_IRIACV.aspx

Publication series

NameIS and T International Symposium on Electronic Imaging Science and Technology

Conference

ConferenceIntelligent Robotics and Industrial Applications using Computer Vision 2019
CountryUnited States
CitySan Francisco
Period13.01.201917.01.2019
Internet address

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