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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Institute of Electrical and Electronics Engineers Inc.
2014
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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/ |
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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. |
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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 |
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Institute of Electrical and Electronics Engineers Inc. |
publishDate |
2014 |
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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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