Foreground extraction for real-time crowd analytics in surveillance system

In this paper, we propose an adaptive background modeling algorithm for crowd surveillance system. We employed Approximate Median Method (AMM) along with the Phase congruency edge detector to develop the background model. The resulting foreground of the proposed model was obtained by applying a logi...

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Main Authors: Hassan, M.A., Malik, A.S., Nicolas, W., Faye, I., Rasheed, W., Nordin, N., Mahmood, M.T.
Format: Conference or Workshop Item
Published: Institute of Electrical and Electronics Engineers Inc. 2014
Online Access:https://www.scopus.com/inward/record.uri?eid=2-s2.0-84907316989&doi=10.1109%2fISCE.2014.6884288&partnerID=40&md5=385758233b35ff5d4cfb72c0f33f3f2e
http://eprints.utp.edu.my/32062/
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spelling my.utp.eprints.320622022-03-29T04:33:50Z Foreground extraction for real-time crowd analytics in surveillance system Hassan, M.A. Malik, A.S. Nicolas, W. Faye, I. Rasheed, W. Nordin, N. Mahmood, M.T. In this paper, we propose an adaptive background modeling algorithm for crowd surveillance system. We employed Approximate Median Method (AMM) along with the Phase congruency edge detector to develop the background model. The resulting foreground of the proposed model was obtained by applying a logical AND operation between binary maps of the (foreground) of the AMM image and the gradient information of the (Phase congruency edge detector) PC. Experimental results demonstrate that the proposed method is highly accurate while providing a processing speed of 24.8 fps allowing its implementation for real time application. © 2014 IEEE. Institute of Electrical and Electronics Engineers Inc. 2014 Conference or Workshop Item NonPeerReviewed https://www.scopus.com/inward/record.uri?eid=2-s2.0-84907316989&doi=10.1109%2fISCE.2014.6884288&partnerID=40&md5=385758233b35ff5d4cfb72c0f33f3f2e Hassan, M.A. and Malik, A.S. and Nicolas, W. and Faye, I. and Rasheed, W. and Nordin, N. and Mahmood, M.T. (2014) Foreground extraction for real-time crowd analytics in surveillance system. In: UNSPECIFIED. http://eprints.utp.edu.my/32062/
institution Universiti Teknologi Petronas
building UTP Resource Centre
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Petronas
content_source UTP Institutional Repository
url_provider http://eprints.utp.edu.my/
description In this paper, we propose an adaptive background modeling algorithm for crowd surveillance system. We employed Approximate Median Method (AMM) along with the Phase congruency edge detector to develop the background model. The resulting foreground of the proposed model was obtained by applying a logical AND operation between binary maps of the (foreground) of the AMM image and the gradient information of the (Phase congruency edge detector) PC. Experimental results demonstrate that the proposed method is highly accurate while providing a processing speed of 24.8 fps allowing its implementation for real time application. © 2014 IEEE.
format Conference or Workshop Item
author Hassan, M.A.
Malik, A.S.
Nicolas, W.
Faye, I.
Rasheed, W.
Nordin, N.
Mahmood, M.T.
spellingShingle Hassan, M.A.
Malik, A.S.
Nicolas, W.
Faye, I.
Rasheed, W.
Nordin, N.
Mahmood, M.T.
Foreground extraction for real-time crowd analytics in surveillance system
author_facet Hassan, M.A.
Malik, A.S.
Nicolas, W.
Faye, I.
Rasheed, W.
Nordin, N.
Mahmood, M.T.
author_sort Hassan, M.A.
title Foreground extraction for real-time crowd analytics in surveillance system
title_short Foreground extraction for real-time crowd analytics in surveillance system
title_full Foreground extraction for real-time crowd analytics in surveillance system
title_fullStr Foreground extraction for real-time crowd analytics in surveillance system
title_full_unstemmed Foreground extraction for real-time crowd analytics in surveillance system
title_sort foreground extraction for real-time crowd analytics in surveillance system
publisher Institute of Electrical and Electronics Engineers Inc.
publishDate 2014
url https://www.scopus.com/inward/record.uri?eid=2-s2.0-84907316989&doi=10.1109%2fISCE.2014.6884288&partnerID=40&md5=385758233b35ff5d4cfb72c0f33f3f2e
http://eprints.utp.edu.my/32062/
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score 13.160551