Video-based abnormal behaviour detection in smart surveillance systems

• Main Authors: Khalifa, Othman Omran, Abdul Khodir, Hazwani, Abdul Malik, Noreha, Abdul Malek, Norun Farihah
• Format: Conference or Workshop Item
• Language: English; English
• Published: Springer 2022
• Subjects: T Technology (General)
• Online Access: http://irep.iium.edu.my/99534/1/99534_Video-based%20abnormal%20behaviour.pdf; http://irep.iium.edu.my/99534/2/99534_Video-based%20abnormal%20behaviour%20_SCOPUS.pdf; http://irep.iium.edu.my/99534/; https://link.springer.com/chapter/10.1007/978-981-16-2406-3_26
• Institution: Universiti Islam Antarabangsa Malaysia

Due to increasing demand for security, the instant detection of abnormal behavior in video surveillance systems becomes a critical issue in a smart surveillance system. The currently applied semiautomatic systems mainly depend on human intervention to detect the abnormal activities and suspicious human behaviours from video context. Due to these limitations, it has become an urgent need for intelligence systems to avoid the very slow response and reduce the human observer and interventions. In this paper, a method that can trace abnormalities of human behaviour from video is presented. Techniques related to bounding box measurements and descriptions for behaviour representation were used. Moreover, the performance evaluation of the proposed method is presented.