Khelifi, A;
Ciccone, G;
Altaweel, M;
Basmaji, T;
(2021)
Autonomous Service Drones for Multimodal Detection and Monitoring of Archaeological Sites.
Applied Sciences
, 11
(21)
, Article 10424. 10.3390/app112110424.
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Abstract
Constant detection and monitoring of archaeological sites and objects have always been an important national goal for many countries. The early identification of changes is crucial to preventive conservation. Archaeologists have always considered using service drones to automate collecting data on and below the ground surface of archaeological sites, with cost and technical barriers being the main hurdles against the wide-scale deployment. Advances in thermal imaging, depth imaging, drones, and artificial intelligence have driven the cost down and improved the quality and volume of data collected and processed. This paper proposes an end-to-end framework for archaeological sites detection and monitoring using autonomous service drones. We mount RGB, depth, and thermal cameras on an autonomous drone for low-altitude data acquisition. To align and aggregate collected images, we propose two-stage multimodal depth-to-RGB and thermal-to-RGB mosaicking algorithms. We then apply detection algorithms to the stitched images to identify change regions and design a user interface to monitor these regions over time. Our results show we can create overlays of aligned thermal and depth data on RGB mosaics of archaeological sites. We tested our change detection algorithm and found it has a root mean square error of 0.04. To validate the proposed framework, we tested our thermal image stitching pipeline against state-of-the-art commercial software. We cost-effectively replicated its functionality while adding a new depth-based modality and created a user interface for temporally monitoring changes in multimodal views of archaeological sites.
Type: | Article |
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Title: | Autonomous Service Drones for Multimodal Detection and Monitoring of Archaeological Sites |
Open access status: | An open access version is available from UCL Discovery |
DOI: | 10.3390/app112110424 |
Publisher version: | https://doi.org/10.3390/app112110424 |
Language: | English |
Additional information: | © 2021 MDPI. This is an open access article distributed under the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/). |
Keywords: | aerial monitoring; unmanned aerial vehicles; mosaicking; cultural heritage detection; photogrammetry; open-source software |
UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL SLASH UCL > Provost and Vice Provost Offices > UCL SLASH > Faculty of S&HS UCL > Provost and Vice Provost Offices > UCL SLASH > Faculty of S&HS > Institute of Archaeology UCL > Provost and Vice Provost Offices > UCL SLASH > Faculty of S&HS > Institute of Archaeology > Institute of Archaeology Gordon Square |
URI: | https://discovery-pp.ucl.ac.uk/id/eprint/10137830 |
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