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STEPS: An Indoor Navigation Framework for Mobile Devices
This paper presents a vision-based navigation system designed for indoor localization. The suggested framework works as a standalone [Formula: see text] positioning system by fusing a sophisticated optical-flow pedometry with map constrains using an advanced particle filter. The presented method req...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7411820/ https://www.ncbi.nlm.nih.gov/pubmed/32679698 http://dx.doi.org/10.3390/s20143929 |
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author | Landau, Yael Ben-Moshe, Boaz |
author_facet | Landau, Yael Ben-Moshe, Boaz |
author_sort | Landau, Yael |
collection | PubMed |
description | This paper presents a vision-based navigation system designed for indoor localization. The suggested framework works as a standalone [Formula: see text] positioning system by fusing a sophisticated optical-flow pedometry with map constrains using an advanced particle filter. The presented method requires no personal calibration and works on standard smartphones with relatively low energy consumption. Field experiments on Android smartphones show that the expected [Formula: see text] error is about 1–2 m in most real-life scenarios. |
format | Online Article Text |
id | pubmed-7411820 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-74118202020-08-25 STEPS: An Indoor Navigation Framework for Mobile Devices Landau, Yael Ben-Moshe, Boaz Sensors (Basel) Article This paper presents a vision-based navigation system designed for indoor localization. The suggested framework works as a standalone [Formula: see text] positioning system by fusing a sophisticated optical-flow pedometry with map constrains using an advanced particle filter. The presented method requires no personal calibration and works on standard smartphones with relatively low energy consumption. Field experiments on Android smartphones show that the expected [Formula: see text] error is about 1–2 m in most real-life scenarios. MDPI 2020-07-15 /pmc/articles/PMC7411820/ /pubmed/32679698 http://dx.doi.org/10.3390/s20143929 Text en © 2020 by the authors. 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 (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Landau, Yael Ben-Moshe, Boaz STEPS: An Indoor Navigation Framework for Mobile Devices |
title | STEPS: An Indoor Navigation Framework for Mobile Devices |
title_full | STEPS: An Indoor Navigation Framework for Mobile Devices |
title_fullStr | STEPS: An Indoor Navigation Framework for Mobile Devices |
title_full_unstemmed | STEPS: An Indoor Navigation Framework for Mobile Devices |
title_short | STEPS: An Indoor Navigation Framework for Mobile Devices |
title_sort | steps: an indoor navigation framework for mobile devices |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7411820/ https://www.ncbi.nlm.nih.gov/pubmed/32679698 http://dx.doi.org/10.3390/s20143929 |
work_keys_str_mv | AT landauyael stepsanindoornavigationframeworkformobiledevices AT benmosheboaz stepsanindoornavigationframeworkformobiledevices |