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A Novel Device-Free Counting Method Based on Channel Status Information

Crowd counting is of significant importance for numerous applications, e.g., urban security, intelligent surveillance and crowd management. Existing crowd counting methods typically require specialized hardware deployment and strict operating conditions, thereby hindering their widespread applicatio...

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Detalles Bibliográficos
Autores principales: Li, Junhuai, Tu, Pengjia, Wang, Huaijun, Wang, Kan, Yu, Lei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6263397/
https://www.ncbi.nlm.nih.gov/pubmed/30445804
http://dx.doi.org/10.3390/s18113981
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author Li, Junhuai
Tu, Pengjia
Wang, Huaijun
Wang, Kan
Yu, Lei
author_facet Li, Junhuai
Tu, Pengjia
Wang, Huaijun
Wang, Kan
Yu, Lei
author_sort Li, Junhuai
collection PubMed
description Crowd counting is of significant importance for numerous applications, e.g., urban security, intelligent surveillance and crowd management. Existing crowd counting methods typically require specialized hardware deployment and strict operating conditions, thereby hindering their widespread application. To acquire a more effective crowd counting approach, a device-free counting method based on Channel Status Information (CSI) is proposed. The wavelet domain denoising is introduced to mitigate environment noise. Furthermore, the amplitude or phase covariance matrix is extracted as the eigenmatrix. Moreover, both the spatial diversity and frequency diversity are leveraged to improve detection robustness. At the same experimental environment, the accuracy of the proposed CSI-based method is compared with a renowned crowd counting one, i.e., Electronic Frog Eye: Counting Crowd Using WiFi (FCC). The experimental results reveal an accuracy improvement of 30% over FCC.
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spelling pubmed-62633972018-12-12 A Novel Device-Free Counting Method Based on Channel Status Information Li, Junhuai Tu, Pengjia Wang, Huaijun Wang, Kan Yu, Lei Sensors (Basel) Article Crowd counting is of significant importance for numerous applications, e.g., urban security, intelligent surveillance and crowd management. Existing crowd counting methods typically require specialized hardware deployment and strict operating conditions, thereby hindering their widespread application. To acquire a more effective crowd counting approach, a device-free counting method based on Channel Status Information (CSI) is proposed. The wavelet domain denoising is introduced to mitigate environment noise. Furthermore, the amplitude or phase covariance matrix is extracted as the eigenmatrix. Moreover, both the spatial diversity and frequency diversity are leveraged to improve detection robustness. At the same experimental environment, the accuracy of the proposed CSI-based method is compared with a renowned crowd counting one, i.e., Electronic Frog Eye: Counting Crowd Using WiFi (FCC). The experimental results reveal an accuracy improvement of 30% over FCC. MDPI 2018-11-15 /pmc/articles/PMC6263397/ /pubmed/30445804 http://dx.doi.org/10.3390/s18113981 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
Li, Junhuai
Tu, Pengjia
Wang, Huaijun
Wang, Kan
Yu, Lei
A Novel Device-Free Counting Method Based on Channel Status Information
title A Novel Device-Free Counting Method Based on Channel Status Information
title_full A Novel Device-Free Counting Method Based on Channel Status Information
title_fullStr A Novel Device-Free Counting Method Based on Channel Status Information
title_full_unstemmed A Novel Device-Free Counting Method Based on Channel Status Information
title_short A Novel Device-Free Counting Method Based on Channel Status Information
title_sort novel device-free counting method based on channel status information
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6263397/
https://www.ncbi.nlm.nih.gov/pubmed/30445804
http://dx.doi.org/10.3390/s18113981
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