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-...
| Main Authors: | , , |
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| Format: | Proceeding Paper |
| Language: | English English |
| Published: |
2014
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| Subjects: | |
| Online Access: | 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 |
| _version_ | 1848781628872065024 |
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| author | Ahmed, Tarem Pathan, Al-Sakib Khan Ahmed, Supriyo |
| author_facet | Ahmed, Tarem Pathan, Al-Sakib Khan Ahmed, Supriyo |
| author_sort | Ahmed, Tarem |
| building | IIUM Repository |
| collection | Online Access |
| 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. |
| first_indexed | 2025-11-14T15:52:36Z |
| format | Proceeding Paper |
| id | iium-38560 |
| institution | International Islamic University Malaysia |
| institution_category | Local University |
| language | English English |
| last_indexed | 2025-11-14T15:52:36Z |
| publishDate | 2014 |
| recordtype | eprints |
| repository_type | Digital Repository |
| 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 Proceeding Paper 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 |
| spellingShingle | QA75 Electronic computers. Computer science Ahmed, Tarem Pathan, Al-Sakib Khan Ahmed, Supriyo Adaptive algorithms for automated intruder detection in surveillance networks |
| title | 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_short | Adaptive algorithms for automated intruder detection in surveillance networks |
| title_sort | adaptive algorithms for automated intruder detection in surveillance networks |
| topic | QA75 Electronic computers. Computer science |
| 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 |