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Image-Based Localization Aided Indoor Pedestrian Trajectory Estimation Using Smartphones

Accurately determining pedestrian location in indoor environments using consumer smartphones is a significant step in the development of ubiquitous localization services. Many different map-matching methods have been combined with pedestrian dead reckoning (PDR) to achieve low-cost and bias-free ped...

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Autores principales: Zhou, Yan, Zheng, Xianwei, Chen, Ruizhi, Xiong, Hanjiang, Guo, Sheng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5795839/
https://www.ncbi.nlm.nih.gov/pubmed/29342123
http://dx.doi.org/10.3390/s18010258
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author Zhou, Yan
Zheng, Xianwei
Chen, Ruizhi
Xiong, Hanjiang
Guo, Sheng
author_facet Zhou, Yan
Zheng, Xianwei
Chen, Ruizhi
Xiong, Hanjiang
Guo, Sheng
author_sort Zhou, Yan
collection PubMed
description Accurately determining pedestrian location in indoor environments using consumer smartphones is a significant step in the development of ubiquitous localization services. Many different map-matching methods have been combined with pedestrian dead reckoning (PDR) to achieve low-cost and bias-free pedestrian tracking. However, this works only in areas with dense map constraints and the error accumulates in open areas. In order to achieve reliable localization without map constraints, an improved image-based localization aided pedestrian trajectory estimation method is proposed in this paper. The image-based localization recovers the pose of the camera from the 2D-3D correspondences between the 2D image positions and the 3D points of the scene model, previously reconstructed by a structure-from-motion (SfM) pipeline. This enables us to determine the initial location and eliminate the accumulative error of PDR when an image is successfully registered. However, the image is not always registered since the traditional 2D-to-3D matching rejects more and more correct matches when the scene becomes large. We thus adopt a robust image registration strategy that recovers initially unregistered images by integrating 3D-to-2D search. In the process, the visibility and co-visibility information is adopted to improve the efficiency when searching for the correspondences from both sides. The performance of the proposed method was evaluated through several experiments and the results demonstrate that it can offer highly acceptable pedestrian localization results in long-term tracking, with an error of only 0.56 m, without the need for dedicated infrastructures.
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spelling pubmed-57958392018-02-13 Image-Based Localization Aided Indoor Pedestrian Trajectory Estimation Using Smartphones Zhou, Yan Zheng, Xianwei Chen, Ruizhi Xiong, Hanjiang Guo, Sheng Sensors (Basel) Article Accurately determining pedestrian location in indoor environments using consumer smartphones is a significant step in the development of ubiquitous localization services. Many different map-matching methods have been combined with pedestrian dead reckoning (PDR) to achieve low-cost and bias-free pedestrian tracking. However, this works only in areas with dense map constraints and the error accumulates in open areas. In order to achieve reliable localization without map constraints, an improved image-based localization aided pedestrian trajectory estimation method is proposed in this paper. The image-based localization recovers the pose of the camera from the 2D-3D correspondences between the 2D image positions and the 3D points of the scene model, previously reconstructed by a structure-from-motion (SfM) pipeline. This enables us to determine the initial location and eliminate the accumulative error of PDR when an image is successfully registered. However, the image is not always registered since the traditional 2D-to-3D matching rejects more and more correct matches when the scene becomes large. We thus adopt a robust image registration strategy that recovers initially unregistered images by integrating 3D-to-2D search. In the process, the visibility and co-visibility information is adopted to improve the efficiency when searching for the correspondences from both sides. The performance of the proposed method was evaluated through several experiments and the results demonstrate that it can offer highly acceptable pedestrian localization results in long-term tracking, with an error of only 0.56 m, without the need for dedicated infrastructures. MDPI 2018-01-17 /pmc/articles/PMC5795839/ /pubmed/29342123 http://dx.doi.org/10.3390/s18010258 Text en © 2018 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
Zhou, Yan
Zheng, Xianwei
Chen, Ruizhi
Xiong, Hanjiang
Guo, Sheng
Image-Based Localization Aided Indoor Pedestrian Trajectory Estimation Using Smartphones
title Image-Based Localization Aided Indoor Pedestrian Trajectory Estimation Using Smartphones
title_full Image-Based Localization Aided Indoor Pedestrian Trajectory Estimation Using Smartphones
title_fullStr Image-Based Localization Aided Indoor Pedestrian Trajectory Estimation Using Smartphones
title_full_unstemmed Image-Based Localization Aided Indoor Pedestrian Trajectory Estimation Using Smartphones
title_short Image-Based Localization Aided Indoor Pedestrian Trajectory Estimation Using Smartphones
title_sort image-based localization aided indoor pedestrian trajectory estimation using smartphones
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5795839/
https://www.ncbi.nlm.nih.gov/pubmed/29342123
http://dx.doi.org/10.3390/s18010258
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