Video-based abnormal behaviour detection in smart surveillance systems
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 hu...
Saved in:
| Main Authors: | , , , |
|---|---|
| Format: | Conference or Workshop Item |
| Language: | English English |
| Published: |
Springer
2022
|
| Subjects: | |
| 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 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Institution: | Universiti Islam Antarabangsa Malaysia |
| Language: | English English |
| Summary: | 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. |
|---|