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Author Gerasimos Antzoulatos; Panagiotis Giannakeris; Ilias Koulalis; Anastasios Karakostas; Stefanos Vrochidis; Ioannis Kompatsiaris
Title A Multi-Layer Fusion Approach For Real-Time Fire Severity Assessment Based on Multimedia Incidents Type Conference Article
Year 2020 Publication ISCRAM 2020 Conference Proceedings – 17th International Conference on Information Systems for Crisis Response and Management Abbreviated Journal Iscram 2020
Volume Issue Pages 75-89
Keywords Crisis Management, Real-Time Fire Severity Assessment, Image Recognition, Object Detection, Semantic Segmentation.
Abstract Shock forest fires have short and long-terms devastating impact on the sustainable management and viability of natural, cultural and residential environments, the local and regional economies and societies. Thus, the utilisation of risk-based decision support systems which encapsulate the technological achievements in Geographical Information Systems (GIS) and fire growth simulation models have rapidly increased in the last decades. On the other hand, the rise of image and video capturing technology, the usage mobile and wearable devices, and the availability of large amounts of multimedia in social media or other online repositories has increased the interest in the image understanding domain. Recent computer vision techniques endeavour to solve several societal problems with security and safety domains to be one of the most serious amongst others. Out of the millions of images that exist online in social media or news articles a great deal of them might include the existence of a crisis or emergency event. In this work, we propose a Multi-Layer Fusion framework, for Real-Time Fire Severity Assessment, based on knowledge extracted from the analysis of Fire Multimedia Incidents. Our approach consists of two levels: (a) an Early Fusion level, in which state-of-the-art image understanding techniques are deployed so as to discover fire incidents and objects from images, and (b) the Decision Fusion level which combines multiple fire incident reports aiming to assess the severity of the ongoing fire event. We evaluate our image understanding techniques in a collection of public fire image databases, and generate simulated incidents and feed them to our Decision Fusion level so as to showcase our method's applicability.
Address Information Technologies Institute (ITI) – Centre for Research and Technology Hellas (CERTH); Information Technologies Institute (ITI) – Centre for Research and Technology Hellas (CERTH); Information Technologies Institute (ITI) – Centre for Research and Technology Hellas (CERTH);Information Technologies Institute (ITI) – Centre for Research and Technology Hellas (CERTH);Information Technologies Institute (ITI) – Centre for Research and Technology Hellas (CERTH);Information Technologies Institute (ITI) – Centre for Research and Technology Hellas (CERTH)
Corporate Author Thesis
Publisher Virginia Tech Place of Publication Blacksburg, VA (USA) Editor Amanda Hughes; Fiona McNeill; Christopher W. Zobel
Language English Summary Language English Original Title
Series Editor Series Title Abbreviated Series Title (up)
Series Volume Series Issue Edition
ISSN 978-1-949373-27-8 ISBN 2411-3394 Medium
Track AI Systems for Crisis and Risks Expedition Conference 17th International Conference on Information Systems for Crisis Response and Management
Notes gantzoulatos@iti.gr Approved no
Call Number Serial 2209
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