Automated visual surveillance using kernel tricks

• Main Authors: Ahmed, Tarem, Wei, Xianglin, Ahmed, Supriyo, Pathan, Al-Sakib Khan
• Format: Conference or Workshop Item
• Language: English; English
• Published: 2013
• Subjects: QA75 Electronic computers. Computer science
• Online Access: http://irep.iium.edu.my/31259/1/CVML13_poster.pdf; http://irep.iium.edu.my/31259/4/lettre-confirmation-poster-TAREM.pdf; http://irep.iium.edu.my/31259/; http://www.di.ens.fr/willow/events/cvml2013/CVML2013Posters.pdf
• Institution: Universiti Islam Antarabangsa Malaysia

Extensive network of multimodal surveillance and security sensors prevalent in many places. Task of simultaneously monitoring multiple images tedious and monotonous for a human. Existing algorithms involve high complexities, need significant memory and storage resources, and typically involve custom equipment. We present three algorithms built using kernel machines to perform automated, real-time intruder detection in surveillance systems. Proposed algorithms are adaptive and portable, with computational, storage and memory complexities independent of time, making them naturally suited to online use.