Human motion analysis and classification using radar micro-doppler signatures

The ability to detect and analyze micro motions in human body is a crucial task in surveillance systems. Although video based systems are currently available to address this problem, but they need high computational resources and under good environmental lighting condition to capture high quality im...

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Main Authors: Hematian, A., Yang, Y., Lu, C., Yazdani, S.
Format: Article
Published: Springer Verlag 2016
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Online Access:http://eprints.utm.my/id/eprint/71716/
https://www.scopus.com/inward/record.uri?eid=2-s2.0-84991813303&doi=10.1007%2f978-3-319-33903-0_1&partnerID=40&md5=958795afefa358adc533d555fcca8f7c
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spelling my.utm.717162017-11-21T03:28:05Z http://eprints.utm.my/id/eprint/71716/ Human motion analysis and classification using radar micro-doppler signatures Hematian, A. Yang, Y. Lu, C. Yazdani, S. T Technology (General) The ability to detect and analyze micro motions in human body is a crucial task in surveillance systems. Although video based systems are currently available to address this problem, but they need high computational resources and under good environmental lighting condition to capture high quality images. In this paper, a novel non-parametric method is presented to detect and calculate human gait speed while analyzing human micro motions based on radar micro-Doppler signatures to classify human motions. The analysis was applied to real data captured by 10 GHz radar from real human targets in a parking lot. Each individual was asked to perform different motions like walking, running, holding a bag while running, etc. The analysis of the gathered data revealed the human motion directions, number of steps taken per second, and whether the person is swinging arms while moving or not. Based on human motion structure and limitations, motion profile of each individual was recognizable to find the combinations between walking or running, and holding an object or swinging arms. We conclude that by adopting this method we can detect human motion profiles in radar based on micro motions of arms and legs in human body for surveillance applications in adverse weather conditions. Springer Verlag 2016 Article PeerReviewed Hematian, A. and Yang, Y. and Lu, C. and Yazdani, S. (2016) Human motion analysis and classification using radar micro-doppler signatures. Studies in Computational Intelligence, 654 . pp. 1-10. ISSN 1860-949X https://www.scopus.com/inward/record.uri?eid=2-s2.0-84991813303&doi=10.1007%2f978-3-319-33903-0_1&partnerID=40&md5=958795afefa358adc533d555fcca8f7c
institution Universiti Teknologi Malaysia
building UTM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
url_provider http://eprints.utm.my/
topic T Technology (General)
spellingShingle T Technology (General)
Hematian, A.
Yang, Y.
Lu, C.
Yazdani, S.
Human motion analysis and classification using radar micro-doppler signatures
description The ability to detect and analyze micro motions in human body is a crucial task in surveillance systems. Although video based systems are currently available to address this problem, but they need high computational resources and under good environmental lighting condition to capture high quality images. In this paper, a novel non-parametric method is presented to detect and calculate human gait speed while analyzing human micro motions based on radar micro-Doppler signatures to classify human motions. The analysis was applied to real data captured by 10 GHz radar from real human targets in a parking lot. Each individual was asked to perform different motions like walking, running, holding a bag while running, etc. The analysis of the gathered data revealed the human motion directions, number of steps taken per second, and whether the person is swinging arms while moving or not. Based on human motion structure and limitations, motion profile of each individual was recognizable to find the combinations between walking or running, and holding an object or swinging arms. We conclude that by adopting this method we can detect human motion profiles in radar based on micro motions of arms and legs in human body for surveillance applications in adverse weather conditions.
format Article
author Hematian, A.
Yang, Y.
Lu, C.
Yazdani, S.
author_facet Hematian, A.
Yang, Y.
Lu, C.
Yazdani, S.
author_sort Hematian, A.
title Human motion analysis and classification using radar micro-doppler signatures
title_short Human motion analysis and classification using radar micro-doppler signatures
title_full Human motion analysis and classification using radar micro-doppler signatures
title_fullStr Human motion analysis and classification using radar micro-doppler signatures
title_full_unstemmed Human motion analysis and classification using radar micro-doppler signatures
title_sort human motion analysis and classification using radar micro-doppler signatures
publisher Springer Verlag
publishDate 2016
url http://eprints.utm.my/id/eprint/71716/
https://www.scopus.com/inward/record.uri?eid=2-s2.0-84991813303&doi=10.1007%2f978-3-319-33903-0_1&partnerID=40&md5=958795afefa358adc533d555fcca8f7c
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score 13.18916