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Automated intruder detection from image sequences using minimum volume sets.

Author(s)
Tarem Ahmed Department of Computer Science, International Islamic University Malaysia, Kuala Lumpur, Malaysia
Al-Sakib Khan Pathan Department of Computer Science, International Islamic University Malaysia, Kuala Lumpur, Malaysia
Supriyo Ahmed Department of Electrical and Electronic Engineering, BRAC University, Dhaka, Bangladesh
Xianglin Wei Department of Computer Science and Engineering, PLA University of Science and Technology, Nanjing, China
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.
Publication Details
Page(s) 11-17
DOI DOI not available
Published Journal: International Journal of Communication Networks and Information Security, Volume: 4, Issue: 1, Year: 2012

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