Ahmed, Tarem and Wei, Xianglin and Ahmed, Supriyo and Pathan, Al-Sakib Khan (2012) Automated intruder detection from image sequences using minimum volume sets. International Journal of Communication Networks and Information Security, 4 (1). pp. 11-17. ISSN 2073-607X (O), 2076-0930 (P)
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Abstract
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.
Item Type: | Article (Journal) |
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Additional Information: | 6481/22265 |
Uncontrolled Keywords: | automated surveillance, online anomaly detection, real-time outlier detection, learning algorithms. |
Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science Q Science > QA Mathematics > QA76 Computer software |
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: | 15 Jun 2012 11:09 |
Last Modified: | 15 Jun 2012 11:09 |
URI: | http://irep.iium.edu.my/id/eprint/22265 |
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