Automated intruder detection from image sequences using minimum volume sets

• Main Authors: Ahmed, Tarem, Wei, Xianglin, Ahmed, Supriyo, Pathan, Al-Sakib Khan
• Format: Article
• Language: English
• Published: Kohat University of Science and Technology (KUST), Pakistan 2012
• Subjects: QA75 Electronic computers. Computer science; QA76 Computer software
• Online Access: http://irep.iium.edu.my/22265/4/88-453-1-PB.pdf; http://irep.iium.edu.my/22265/; http://www.ijcnis.org/index.php/ijcnis/article/view/88
• Institution: Universiti Islam Antarabangsa Malaysia

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.