Adaptive algorithms for automated intruder detection in surveillance networks

Many types of automated visual surveillance systems have been presented in the recent literature. Most of the schemes require custom equipment, or involve significant complexity and storage needs. After studying the area in detail, this work presents four novel algorithms to perform automated, real-...

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Main Authors:	Ahmed, Tarem, Pathan, Al-Sakib Khan, Ahmed, Supriyo
Format:	Conference or Workshop Item
Language:	English English
Published:	2014
Subjects:	QA75 Electronic computers. Computer science
Online Access:	http://irep.iium.edu.my/38560/ http://irep.iium.edu.my/38560/ http://irep.iium.edu.my/38560/1/1570001923.pdf http://irep.iium.edu.my/38560/2/FULL_CONF_PROGRAM_%5BICACCI-2014%5D.pdf

id	iium-38560
recordtype	eprints
spelling	iium-385602015-03-25T07:57:45Z http://irep.iium.edu.my/38560/ Adaptive algorithms for automated intruder detection in surveillance networks Ahmed, Tarem Pathan, Al-Sakib Khan Ahmed, Supriyo QA75 Electronic computers. Computer science Many types of automated visual surveillance systems have been presented in the recent literature. Most of the schemes require custom equipment, or involve significant complexity and storage needs. After studying the area in detail, this work presents four novel algorithms to perform automated, real-time intruder detection in surveillance networks. Built using machine learning techniques, the proposed algorithms are adaptive and portable, do not require any expensive or sophisticated component, are lightweight, and efficient with runtimes of the order of hundredths of a second. Two of the proposed algorithms have been developed by us. With application to two complementary data sets and quantitative performance comparisons with two representative existing schemes, we show that it is possible to easily obtain high detection accuracy with low false positives. 2014 Conference or Workshop Item PeerReviewed application/pdf en http://irep.iium.edu.my/38560/1/1570001923.pdf application/pdf en http://irep.iium.edu.my/38560/2/FULL_CONF_PROGRAM_%5BICACCI-2014%5D.pdf Ahmed, Tarem and Pathan, Al-Sakib Khan and Ahmed, Supriyo (2014) Adaptive algorithms for automated intruder detection in surveillance networks. In: ICACCI 2014 Doctoral Consortium; 3rd International Conference on Advances in Computing, Communications & Informatics (ICACCI 2014), September 24-27, 2014, Delhi, India, 24-27 Sept. 2014, Delhi, India. http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=6968617&tag=1
repository_type	Digital Repository
institution_category	Local University
institution	International Islamic University Malaysia
building	IIUM Repository
collection	Online Access
language	English English
topic	QA75 Electronic computers. Computer science
spellingShingle	QA75 Electronic computers. Computer science Ahmed, Tarem Pathan, Al-Sakib Khan Ahmed, Supriyo Adaptive algorithms for automated intruder detection in surveillance networks
description	Many types of automated visual surveillance systems have been presented in the recent literature. Most of the schemes require custom equipment, or involve significant complexity and storage needs. After studying the area in detail, this work presents four novel algorithms to perform automated, real-time intruder detection in surveillance networks. Built using machine learning techniques, the proposed algorithms are adaptive and portable, do not require any expensive or sophisticated component, are lightweight, and efficient with runtimes of the order of hundredths of a second. Two of the proposed algorithms have been developed by us. With application to two complementary data sets and quantitative performance comparisons with two representative existing schemes, we show that it is possible to easily obtain high detection accuracy with low false positives.
format	Conference or Workshop Item
author	Ahmed, Tarem Pathan, Al-Sakib Khan Ahmed, Supriyo
author_facet	Ahmed, Tarem Pathan, Al-Sakib Khan Ahmed, Supriyo
author_sort	Ahmed, Tarem
title	Adaptive algorithms for automated intruder detection in surveillance networks
title_short	Adaptive algorithms for automated intruder detection in surveillance networks
title_full	Adaptive algorithms for automated intruder detection in surveillance networks
title_fullStr	Adaptive algorithms for automated intruder detection in surveillance networks
title_full_unstemmed	Adaptive algorithms for automated intruder detection in surveillance networks
title_sort	adaptive algorithms for automated intruder detection in surveillance networks
publishDate	2014
url	http://irep.iium.edu.my/38560/ http://irep.iium.edu.my/38560/ http://irep.iium.edu.my/38560/1/1570001923.pdf http://irep.iium.edu.my/38560/2/FULL_CONF_PROGRAM_%5BICACCI-2014%5D.pdf
first_indexed	2023-09-18T20:55:24Z
last_indexed	2023-09-18T20:55:24Z
_version_	1777410270381998080

Adaptive algorithms for automated intruder detection in surveillance networks

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