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Multitarget Detection and Tracking Method in Remote Sensing Satellite Video

A remote sensing video satellite multiple object detection and tracking method based on road masking, Gaussian mixture model (GMM), and data association is proposed. This method first extracts the road network from the remote sensing video based on deep learning. In the detection stage, the backgrou...

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Detalles Bibliográficos
Autores principales: Lei, Lei, Guo, Dongen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8426105/
https://www.ncbi.nlm.nih.gov/pubmed/34512746
http://dx.doi.org/10.1155/2021/7381909
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author Lei, Lei
Guo, Dongen
author_facet Lei, Lei
Guo, Dongen
author_sort Lei, Lei
collection PubMed
description A remote sensing video satellite multiple object detection and tracking method based on road masking, Gaussian mixture model (GMM), and data association is proposed. This method first extracts the road network from the remote sensing video based on deep learning. In the detection stage, the background subtraction algorithm is used based on the GMM to obtain the detection results of the moving targets on the road. In the tracking stage, the data association of the same target detection result in adjacent frames is realized based on the neighborhood search algorithm, so as to obtain the continuous tracking trajectory of each target. The experiments about multiobject detection and tracking are conducted on data measure by real remote sensing satellites, and the results verified the feasibility of the proposed method.
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spelling pubmed-84261052021-09-09 Multitarget Detection and Tracking Method in Remote Sensing Satellite Video Lei, Lei Guo, Dongen Comput Intell Neurosci Research Article A remote sensing video satellite multiple object detection and tracking method based on road masking, Gaussian mixture model (GMM), and data association is proposed. This method first extracts the road network from the remote sensing video based on deep learning. In the detection stage, the background subtraction algorithm is used based on the GMM to obtain the detection results of the moving targets on the road. In the tracking stage, the data association of the same target detection result in adjacent frames is realized based on the neighborhood search algorithm, so as to obtain the continuous tracking trajectory of each target. The experiments about multiobject detection and tracking are conducted on data measure by real remote sensing satellites, and the results verified the feasibility of the proposed method. Hindawi 2021-08-31 /pmc/articles/PMC8426105/ /pubmed/34512746 http://dx.doi.org/10.1155/2021/7381909 Text en Copyright © 2021 Lei Lei and Dongen Guo. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Lei, Lei
Guo, Dongen
Multitarget Detection and Tracking Method in Remote Sensing Satellite Video
title Multitarget Detection and Tracking Method in Remote Sensing Satellite Video
title_full Multitarget Detection and Tracking Method in Remote Sensing Satellite Video
title_fullStr Multitarget Detection and Tracking Method in Remote Sensing Satellite Video
title_full_unstemmed Multitarget Detection and Tracking Method in Remote Sensing Satellite Video
title_short Multitarget Detection and Tracking Method in Remote Sensing Satellite Video
title_sort multitarget detection and tracking method in remote sensing satellite video
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8426105/
https://www.ncbi.nlm.nih.gov/pubmed/34512746
http://dx.doi.org/10.1155/2021/7381909
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