Adaptive algorithms for automated intruder detection in surveillance networks

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.

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Abstract

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.

Item Type:	Conference or Workshop Item (Full Paper)
Additional Information:	6481/38560 (ISBN: 978-1-4799-3078-4, DOI: 10.1109/ICACCI.2014.6968617)
Uncontrolled Keywords:	Automated intruder detection, surveillance networks
Subjects:	Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button):	Kulliyyah of Information and Communication Technology > Department of Computer Science Kulliyyah of Information and Communication Technology > Department of Computer Science
Depositing User:	Dr. Al-Sakib Khan Pathan
Date Deposited:	02 Oct 2014 16:33
Last Modified:	25 Mar 2015 15:57
URI:	http://irep.iium.edu.my/id/eprint/38560

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