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| Titre: | Strategy of detecting abnormal behaviors by fuzzy logic |
| Auteur(s): | Chebi, Hocine
Acheli, Dalila
Kesraoui, Mohamed |
| Mots-clés: | Abnormal behavior detection
Videos
Segmentation |
| Date de publication: | 2017 |
| Editeur: | IEEE |
| Collection/Numéro: | 2017 Intelligent Systems and Computer Vision (ISCV); |
| Résumé: | This work falls within the framework of the video surveillance research axis. This work falls within the scope of video surveillance. It involves a link between automatic processing and problems related to video surveillance. The job is to analyze video streams coming from a network of surveillance cameras, deployed in an area of interest in order to detect abnormal behavior. Our approach in this article relies on the new application and the use of fuzzy logic in the case of division and fusion of the crowd. The detection of these behaviors will increase the speed of response of the security services in order to perform accurate analysis and detection of events in real time |
| URI/URL: | https://ieeexplore.ieee.org/document/8054982
DOI: 10.1109/ISACV.2017.8054982
http://dlibrary.univ-boumerdes.dz:8080/handle/123456789/6708 |
| ISBN: | 978-1-5090-4063-6
Electronic ISBN:978-1-5090-4062-9 |
| Collection(s) : | Communications Internationales
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