Adaptive algorithms for automated intruder detection in surveillance networks
This conference paper was presented in the 3rd International Conference on Advances in Computing, Communications and Informatics, ICACCI 2014; Delhi; India; 24 September 2014 through 27 September 2014 [© 2014 Institute of Electrical and Electronics Engineers Inc.] The conference paper's definit...
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© 2014 Institute of Electrical and Electronics Engineers Inc.
2016
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| Accès en ligne: | http://hdl.handle.net/10361/7033 |
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10361-70332016-11-29T08:51:59Z Adaptive algorithms for automated intruder detection in surveillance networks Ahmed, Tarem Ahmed, Supriyo Sabbir Pathan, Al-Sakib Khan Department of Electrical and Electronic Engineering This conference paper was presented in the 3rd International Conference on Advances in Computing, Communications and Informatics, ICACCI 2014; Delhi; India; 24 September 2014 through 27 September 2014 [© 2014 Institute of Electrical and Electronics Engineers Inc.] The conference paper's definite version is available at: http:// 10.1109/ICACCI.2014.6968617 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. Published 2016-11-29T08:50:18Z 2016-11-29T08:50:18Z 2014 Conference Paper Ahmed, T., Pathan, A. -. K., & Ahmed, S. (2014). Adaptive algorithms for automated intruder detection in surveillance networks. Paper presented at the Proceedings of the 2014 International Conference on Advances in Computing, Communications and Informatics, ICACCI 2014, 2775-2780. doi:10.1109/ICACCI.2014.6968617 978-147993079-1 http://hdl.handle.net/10361/7033 10.1109/ICACCI.2014.6968617 en http://ieeexplore.ieee.org/document/6968617/ © 2014 Institute of Electrical and Electronics Engineers Inc. |
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Brac University |
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Institutional Repository |
| language |
English |
| description |
This conference paper was presented in the 3rd International Conference on Advances in Computing, Communications and Informatics, ICACCI 2014; Delhi; India; 24 September 2014 through 27 September 2014 [© 2014 Institute of Electrical and Electronics Engineers Inc.] The conference paper's definite version is available at: http:// 10.1109/ICACCI.2014.6968617 |
| author2 |
Department of Electrical and Electronic Engineering |
| author_facet |
Department of Electrical and Electronic Engineering Ahmed, Tarem Ahmed, Supriyo Sabbir Pathan, Al-Sakib Khan |
| format |
Conference Paper |
| author |
Ahmed, Tarem Ahmed, Supriyo Sabbir Pathan, Al-Sakib Khan |
| spellingShingle |
Ahmed, Tarem Ahmed, Supriyo Sabbir Pathan, Al-Sakib Khan Adaptive algorithms for automated intruder detection in surveillance networks |
| 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 |
| publisher |
© 2014 Institute of Electrical and Electronics Engineers Inc. |
| publishDate |
2016 |
| url |
http://hdl.handle.net/10361/7033 |
| work_keys_str_mv |
AT ahmedtarem adaptivealgorithmsforautomatedintruderdetectioninsurveillancenetworks AT ahmedsupriyosabbir adaptivealgorithmsforautomatedintruderdetectioninsurveillancenetworks AT pathanalsakibkhan adaptivealgorithmsforautomatedintruderdetectioninsurveillancenetworks |
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