Supporting first responders in emergencies using computer vision and drones

Ning Zhang*

*Corresponding author for this work

Research output: ThesisPhD Thesis - Research UT, graduation UT

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Abstract

First responders (FRs) are the first to arrive after a disaster. It is dangerous for them to enter the disaster area without knowing anything about the situation. In order to improve FRs' situational awareness of the emergency environment and to facilitate their rescue planning, the European Union launched INGENIOUS, a project aimed at developing the Next Generation Integrated Toolkit (NGIT) for emergency services of the future. Work Package 3 of the INGENIOUS project was to develop "smart devices in the air and on the ground". As one of the partners in this work package, our aim was to develop computer vision algorithms for scene understanding to support the decision-making and rescue of FRs. Although computer vision had gained a great deal of attention in recent years, its applications in disaster scenarios were limited, and existing methods did not meet FRs' specific requirements. To this end, This dissertation developed several novel computer vision algorithms to support FRs' post-disaster missions within the INGENIOUS project.
Original languageEnglish
QualificationDoctor of Philosophy
Awarding Institution
  • University of Twente
  • Faculty of Geo-Information Science and Earth Observation
Supervisors/Advisors
  • Kerle, Norman, Supervisor
  • Vosselman, George, Supervisor
  • Nex, Francesco, Supervisor
Award date1 Nov 2023
Place of PublicationEnschede
Publisher
Print ISBNs978-90-365-5843-3
Electronic ISBNs978-90-365-5844-0
DOIs
Publication statusPublished - 1 Nov 2023

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