Mixture of Gaussian based background modelling for crowd tracking using multiple cameras

Visual surveillance system for tracking crowd using multiple cameras at dynamic backgrounds faces many challenges such as illumination variance, occultation, low spatial temporal resolution, sleeping person, shadows and camera noise. In this paper we address the issue of gradual and sudden illuminat...

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Main Authors: Hassan, M.A., Malik, A.S., Nicolas, W., Faye, I., Mahmood, M.T.
Format: Conference or Workshop Item
Published: IEEE Computer Society 2014
Online Access:https://www.scopus.com/inward/record.uri?eid=2-s2.0-84906350445&doi=10.1109%2fICIAS.2014.6869457&partnerID=40&md5=9d9f2644fa955d4649bb66d502127249
http://eprints.utp.edu.my/32109/
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spelling my.utp.eprints.321092022-03-29T04:34:49Z Mixture of Gaussian based background modelling for crowd tracking using multiple cameras Hassan, M.A. Malik, A.S. Nicolas, W. Faye, I. Mahmood, M.T. Visual surveillance system for tracking crowd using multiple cameras at dynamic backgrounds faces many challenges such as illumination variance, occultation, low spatial temporal resolution, sleeping person, shadows and camera noise. In this paper we address the issue of gradual and sudden illumination variance caused by movement of the sun and the clouds. We evaluate Mixture of Gaussian method and background modelling method for extracting foreground from the background for crowd related data base. We have evaluated the performance of the background model for sparse and dense crowds to evaluate the accuracy and efficiency of the model subjectively for crowd analytics based scenarios. © 2014 IEEE. IEEE Computer Society 2014 Conference or Workshop Item NonPeerReviewed https://www.scopus.com/inward/record.uri?eid=2-s2.0-84906350445&doi=10.1109%2fICIAS.2014.6869457&partnerID=40&md5=9d9f2644fa955d4649bb66d502127249 Hassan, M.A. and Malik, A.S. and Nicolas, W. and Faye, I. and Mahmood, M.T. (2014) Mixture of Gaussian based background modelling for crowd tracking using multiple cameras. In: UNSPECIFIED. http://eprints.utp.edu.my/32109/
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 Visual surveillance system for tracking crowd using multiple cameras at dynamic backgrounds faces many challenges such as illumination variance, occultation, low spatial temporal resolution, sleeping person, shadows and camera noise. In this paper we address the issue of gradual and sudden illumination variance caused by movement of the sun and the clouds. We evaluate Mixture of Gaussian method and background modelling method for extracting foreground from the background for crowd related data base. We have evaluated the performance of the background model for sparse and dense crowds to evaluate the accuracy and efficiency of the model subjectively for crowd analytics based scenarios. © 2014 IEEE.
format Conference or Workshop Item
author Hassan, M.A.
Malik, A.S.
Nicolas, W.
Faye, I.
Mahmood, M.T.
spellingShingle Hassan, M.A.
Malik, A.S.
Nicolas, W.
Faye, I.
Mahmood, M.T.
Mixture of Gaussian based background modelling for crowd tracking using multiple cameras
author_facet Hassan, M.A.
Malik, A.S.
Nicolas, W.
Faye, I.
Mahmood, M.T.
author_sort Hassan, M.A.
title Mixture of Gaussian based background modelling for crowd tracking using multiple cameras
title_short Mixture of Gaussian based background modelling for crowd tracking using multiple cameras
title_full Mixture of Gaussian based background modelling for crowd tracking using multiple cameras
title_fullStr Mixture of Gaussian based background modelling for crowd tracking using multiple cameras
title_full_unstemmed Mixture of Gaussian based background modelling for crowd tracking using multiple cameras
title_sort mixture of gaussian based background modelling for crowd tracking using multiple cameras
publisher IEEE Computer Society
publishDate 2014
url https://www.scopus.com/inward/record.uri?eid=2-s2.0-84906350445&doi=10.1109%2fICIAS.2014.6869457&partnerID=40&md5=9d9f2644fa955d4649bb66d502127249
http://eprints.utp.edu.my/32109/
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