Automated intruder detection from image sequences using minimum volume sets

This article was published in the International Journal of Communication Networks and Information Security [© 2014 IJCNIS] and The Article's website is at: http://www.ijcnis.org/index.php/ijcnis/article/view/88

Manylion Llyfryddiaeth
Prif Awduron:	Ahmed, Tarem, Wei, Xianglin, Ahmed, Supriyo Sabbir, Pathan, Al-Sakib Khan
Awduron Eraill:	Department of Electrical and Electronic Engineering, BRAC University
Fformat:	Erthygl
Iaith:	English
Cyhoeddwyd:	© 2012 International Journal of Communication Networks and Information Security 2016
Pynciau:	Automated surveillance Learning algorithms Online anomaly detection Real-time outlier detection
Mynediad Ar-lein:	http://hdl.handle.net/10361/7206

id	10361-7206
record_format	dspace
spelling	10361-72062016-12-12T08:40:36Z Automated intruder detection from image sequences using minimum volume sets Ahmed, Tarem Wei, Xianglin Ahmed, Supriyo Sabbir Pathan, Al-Sakib Khan Department of Electrical and Electronic Engineering, BRAC University Automated surveillance Learning algorithms Online anomaly detection Real-time outlier detection This article was published in the International Journal of Communication Networks and Information Security [© 2014 IJCNIS] and The Article's website is at: http://www.ijcnis.org/index.php/ijcnis/article/view/88 We propose a new algorithm based on machine learning techniques for automatic intruder detection in visual surveillance networks. The proposed algorithm is theoretically founded on the concept of Minimum Volume Sets. Through application to image sequences from two different scenarios and comparison with existing algorithms, we show that it is possible for our proposed algorithm to easily obtain high detection accuracy with low false alarm rates. Published 2016-12-12T08:39:20Z 2016-12-12T08:39:20Z 2012 Article Ahmed, T., Wei, X., Ahmed, S., & Pathan, A. K. (2012). Automated intruder detection from image sequences using minimum volume sets. International Journal of Communication Networks and Information Security, 4(1), 11-17. Retrieved from www.scopus.com 20760930 http://hdl.handle.net/10361/7206 en http://www.ijcnis.org/index.php/ijcnis/article/view/88 © 2012 International Journal of Communication Networks and Information Security
institution	Brac University
collection	Institutional Repository
language	English
topic	Automated surveillance Learning algorithms Online anomaly detection Real-time outlier detection
spellingShingle	Automated surveillance Learning algorithms Online anomaly detection Real-time outlier detection Ahmed, Tarem Wei, Xianglin Ahmed, Supriyo Sabbir Pathan, Al-Sakib Khan Automated intruder detection from image sequences using minimum volume sets
description	This article was published in the International Journal of Communication Networks and Information Security [© 2014 IJCNIS] and The Article's website is at: http://www.ijcnis.org/index.php/ijcnis/article/view/88
author2	Department of Electrical and Electronic Engineering, BRAC University
author_facet	Department of Electrical and Electronic Engineering, BRAC University Ahmed, Tarem Wei, Xianglin Ahmed, Supriyo Sabbir Pathan, Al-Sakib Khan
format	Article
author	Ahmed, Tarem Wei, Xianglin Ahmed, Supriyo Sabbir Pathan, Al-Sakib Khan
author_sort	Ahmed, Tarem
title	Automated intruder detection from image sequences using minimum volume sets
title_short	Automated intruder detection from image sequences using minimum volume sets
title_full	Automated intruder detection from image sequences using minimum volume sets
title_fullStr	Automated intruder detection from image sequences using minimum volume sets
title_full_unstemmed	Automated intruder detection from image sequences using minimum volume sets
title_sort	automated intruder detection from image sequences using minimum volume sets
publisher	© 2012 International Journal of Communication Networks and Information Security
publishDate	2016
url	http://hdl.handle.net/10361/7206
work_keys_str_mv	AT ahmedtarem automatedintruderdetectionfromimagesequencesusingminimumvolumesets AT weixianglin automatedintruderdetectionfromimagesequencesusingminimumvolumesets AT ahmedsupriyosabbir automatedintruderdetectionfromimagesequencesusingminimumvolumesets AT pathanalsakibkhan automatedintruderdetectionfromimagesequencesusingminimumvolumesets
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Automated intruder detection from image sequences using minimum volume sets

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