A review on classifying abnormal behavior in crowd scene

Crowd behavior analysis has become one of the new areas of interest in the computer vision community due to the increasing demands from surveillance and security industries. It is important to meticulously understand crowd behavior to prevent any disaster and unwanted incidents such as thief, stampe...

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Main Authors: Afiq, A.A., Zakariya, M.A., Saad, M.N., Nurfarzana, A.A., Khir, M.H.M., Fadzil, A.F., Jale, A., Gunawan, W., Izuddin, Z.A.A., Faizari, M.
Format: Article
Institution: Universiti Teknologi Petronas
Record Id / ISBN-0: utp-eprints.22211 /
Published: 2019
Online Access: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85058057075&doi=10.1016%2fj.jvcir.2018.11.035&partnerID=40&md5=d4386619b0e9dbdfb33d13c9d61505a8
http://eprints.utp.edu.my/22211/
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id utp-eprints.22211
recordtype eprints
spelling utp-eprints.222112019-02-28T05:06:29Z A review on classifying abnormal behavior in crowd scene Afiq, A.A. Zakariya, M.A. Saad, M.N. Nurfarzana, A.A. Khir, M.H.M. Fadzil, A.F. Jale, A. Gunawan, W. Izuddin, Z.A.A. Faizari, M. Crowd behavior analysis has become one of the new areas of interest in the computer vision community due to the increasing demands from surveillance and security industries. It is important to meticulously understand crowd behavior to prevent any disaster and unwanted incidents such as thief, stampede and riots. For this purpose, crowd features such as density, motion and trajectory are analyzed to detect any abnormality in the crowd. Thus, this review is aimed to provide insight on several detection methods including Gaussian Mixture Model (GMM), Hidden Markov Model (HMM), Optical Flow method and Spatio-Temporal Technique (STT). Providing the latest development, the review presented the studies that are published in journals and conferences over the past 5 years. © 2018 Elsevier Inc. 2019 Article NonPeerReviewed https://www.scopus.com/inward/record.uri?eid=2-s2.0-85058057075&doi=10.1016%2fj.jvcir.2018.11.035&partnerID=40&md5=d4386619b0e9dbdfb33d13c9d61505a8 Afiq, A.A. and Zakariya, M.A. and Saad, M.N. and Nurfarzana, A.A. and Khir, M.H.M. and Fadzil, A.F. and Jale, A. and Gunawan, W. and Izuddin, Z.A.A. and Faizari, M. (2019) A review on classifying abnormal behavior in crowd scene. Journal of Visual Communication and Image Representation, 58 . pp. 285-303. http://eprints.utp.edu.my/22211/
institution Universiti Teknologi Petronas
collection UTP Institutional Repository
description Crowd behavior analysis has become one of the new areas of interest in the computer vision community due to the increasing demands from surveillance and security industries. It is important to meticulously understand crowd behavior to prevent any disaster and unwanted incidents such as thief, stampede and riots. For this purpose, crowd features such as density, motion and trajectory are analyzed to detect any abnormality in the crowd. Thus, this review is aimed to provide insight on several detection methods including Gaussian Mixture Model (GMM), Hidden Markov Model (HMM), Optical Flow method and Spatio-Temporal Technique (STT). Providing the latest development, the review presented the studies that are published in journals and conferences over the past 5 years. © 2018 Elsevier Inc.
format Article
author Afiq, A.A.
Zakariya, M.A.
Saad, M.N.
Nurfarzana, A.A.
Khir, M.H.M.
Fadzil, A.F.
Jale, A.
Gunawan, W.
Izuddin, Z.A.A.
Faizari, M.
spellingShingle Afiq, A.A.
Zakariya, M.A.
Saad, M.N.
Nurfarzana, A.A.
Khir, M.H.M.
Fadzil, A.F.
Jale, A.
Gunawan, W.
Izuddin, Z.A.A.
Faizari, M.
A review on classifying abnormal behavior in crowd scene
author_sort Afiq, A.A.
title A review on classifying abnormal behavior in crowd scene
title_short A review on classifying abnormal behavior in crowd scene
title_full A review on classifying abnormal behavior in crowd scene
title_fullStr A review on classifying abnormal behavior in crowd scene
title_full_unstemmed A review on classifying abnormal behavior in crowd scene
title_sort review on classifying abnormal behavior in crowd scene
publishDate 2019
url https://www.scopus.com/inward/record.uri?eid=2-s2.0-85058057075&doi=10.1016%2fj.jvcir.2018.11.035&partnerID=40&md5=d4386619b0e9dbdfb33d13c9d61505a8
http://eprints.utp.edu.my/22211/
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score 11.62408