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Near Real-Time Volumetric Estimates Using Unmanned Aerial Platforms Equipped with Depth and Tracking Sensors
Volume estimation of specific objects via close-range remote sensing is a complex task requiring expensive hardware and/or significant computational burden, often discouraging users potentially interested in the technology. This paper presents an innovative system for cost-effective near real-time v...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9737846/ https://www.ncbi.nlm.nih.gov/pubmed/36502163 http://dx.doi.org/10.3390/s22239462 |
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author | Amitrano, Donato Cicala, Luca Cuciniello, Giovanni De Mizio, Marco Poderico, Mariana Tufano, Francesco |
author_facet | Amitrano, Donato Cicala, Luca Cuciniello, Giovanni De Mizio, Marco Poderico, Mariana Tufano, Francesco |
author_sort | Amitrano, Donato |
collection | PubMed |
description | Volume estimation of specific objects via close-range remote sensing is a complex task requiring expensive hardware and/or significant computational burden, often discouraging users potentially interested in the technology. This paper presents an innovative system for cost-effective near real-time volume estimation based on a custom platform equipped with depth and tracking cameras. Its performance has been tested in different application-oriented scenarios and compared against measurements and state-of-the-art photogrammetry. The comparison showed that the developed architecture is able to provide estimates fully comparable with the benchmark, resulting in a quick, reliable and cost-effective solution to the problem of volumetric estimates within the functioning range of the exploited sensors. |
format | Online Article Text |
id | pubmed-9737846 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-97378462022-12-11 Near Real-Time Volumetric Estimates Using Unmanned Aerial Platforms Equipped with Depth and Tracking Sensors Amitrano, Donato Cicala, Luca Cuciniello, Giovanni De Mizio, Marco Poderico, Mariana Tufano, Francesco Sensors (Basel) Article Volume estimation of specific objects via close-range remote sensing is a complex task requiring expensive hardware and/or significant computational burden, often discouraging users potentially interested in the technology. This paper presents an innovative system for cost-effective near real-time volume estimation based on a custom platform equipped with depth and tracking cameras. Its performance has been tested in different application-oriented scenarios and compared against measurements and state-of-the-art photogrammetry. The comparison showed that the developed architecture is able to provide estimates fully comparable with the benchmark, resulting in a quick, reliable and cost-effective solution to the problem of volumetric estimates within the functioning range of the exploited sensors. MDPI 2022-12-03 /pmc/articles/PMC9737846/ /pubmed/36502163 http://dx.doi.org/10.3390/s22239462 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Amitrano, Donato Cicala, Luca Cuciniello, Giovanni De Mizio, Marco Poderico, Mariana Tufano, Francesco Near Real-Time Volumetric Estimates Using Unmanned Aerial Platforms Equipped with Depth and Tracking Sensors |
title | Near Real-Time Volumetric Estimates Using Unmanned Aerial Platforms Equipped with Depth and Tracking Sensors |
title_full | Near Real-Time Volumetric Estimates Using Unmanned Aerial Platforms Equipped with Depth and Tracking Sensors |
title_fullStr | Near Real-Time Volumetric Estimates Using Unmanned Aerial Platforms Equipped with Depth and Tracking Sensors |
title_full_unstemmed | Near Real-Time Volumetric Estimates Using Unmanned Aerial Platforms Equipped with Depth and Tracking Sensors |
title_short | Near Real-Time Volumetric Estimates Using Unmanned Aerial Platforms Equipped with Depth and Tracking Sensors |
title_sort | near real-time volumetric estimates using unmanned aerial platforms equipped with depth and tracking sensors |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9737846/ https://www.ncbi.nlm.nih.gov/pubmed/36502163 http://dx.doi.org/10.3390/s22239462 |
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