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Bayesian Estimation-Based Pedestrian Tracking in Microcells
We consider a pedestrian tracking system where sensor nodes are placed only at specific points so that the monitoring region is divided into multiple smaller regions referred to as microcells. In the proposed pedestrian tracking system, sensor nodes composed of pairs of binary sensors can detect ped...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi Publishing Corporation
2013
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3800566/ https://www.ncbi.nlm.nih.gov/pubmed/24204202 http://dx.doi.org/10.1155/2013/187479 |
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author | Taniguchi, Yoshiaki Sasabe, Masahiro Aihara, Satoshi Nakano, Hirotaka |
author_facet | Taniguchi, Yoshiaki Sasabe, Masahiro Aihara, Satoshi Nakano, Hirotaka |
author_sort | Taniguchi, Yoshiaki |
collection | PubMed |
description | We consider a pedestrian tracking system where sensor nodes are placed only at specific points so that the monitoring region is divided into multiple smaller regions referred to as microcells. In the proposed pedestrian tracking system, sensor nodes composed of pairs of binary sensors can detect pedestrian arrival and departure events. In this paper, we focus on pedestrian tracking in microcells. First, we investigate actual pedestrian trajectories in a microcell on the basis of observations using video sequences, after which we prepare a pedestrian mobility model. Next, we propose a method for pedestrian tracking in microcells based on the developed pedestrian mobility model. In the proposed method, we extend the Bayesian estimation to account for time-series information to estimate the correspondence between pedestrian arrival and departure events. Through simulations, we show that the tracking success ratio of the proposed method is increased by 35.8% compared to a combinatorial optimization-based tracking method. |
format | Online Article Text |
id | pubmed-3800566 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2013 |
publisher | Hindawi Publishing Corporation |
record_format | MEDLINE/PubMed |
spelling | pubmed-38005662013-11-07 Bayesian Estimation-Based Pedestrian Tracking in Microcells Taniguchi, Yoshiaki Sasabe, Masahiro Aihara, Satoshi Nakano, Hirotaka ScientificWorldJournal Research Article We consider a pedestrian tracking system where sensor nodes are placed only at specific points so that the monitoring region is divided into multiple smaller regions referred to as microcells. In the proposed pedestrian tracking system, sensor nodes composed of pairs of binary sensors can detect pedestrian arrival and departure events. In this paper, we focus on pedestrian tracking in microcells. First, we investigate actual pedestrian trajectories in a microcell on the basis of observations using video sequences, after which we prepare a pedestrian mobility model. Next, we propose a method for pedestrian tracking in microcells based on the developed pedestrian mobility model. In the proposed method, we extend the Bayesian estimation to account for time-series information to estimate the correspondence between pedestrian arrival and departure events. Through simulations, we show that the tracking success ratio of the proposed method is increased by 35.8% compared to a combinatorial optimization-based tracking method. Hindawi Publishing Corporation 2013-09-24 /pmc/articles/PMC3800566/ /pubmed/24204202 http://dx.doi.org/10.1155/2013/187479 Text en Copyright © 2013 Yoshiaki Taniguchi et al. https://creativecommons.org/licenses/by/3.0/ 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 Taniguchi, Yoshiaki Sasabe, Masahiro Aihara, Satoshi Nakano, Hirotaka Bayesian Estimation-Based Pedestrian Tracking in Microcells |
title | Bayesian Estimation-Based Pedestrian Tracking in Microcells |
title_full | Bayesian Estimation-Based Pedestrian Tracking in Microcells |
title_fullStr | Bayesian Estimation-Based Pedestrian Tracking in Microcells |
title_full_unstemmed | Bayesian Estimation-Based Pedestrian Tracking in Microcells |
title_short | Bayesian Estimation-Based Pedestrian Tracking in Microcells |
title_sort | bayesian estimation-based pedestrian tracking in microcells |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3800566/ https://www.ncbi.nlm.nih.gov/pubmed/24204202 http://dx.doi.org/10.1155/2013/187479 |
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