Strategy of detecting abnormal behaviors by fuzzy logic

dc.contributor.author	Chebi, Hocine
dc.contributor.author	Acheli, Dalila
dc.contributor.author	Kesraoui, Mohamed
dc.date.accessioned	2021-03-28T08:25:38Z
dc.date.available	2021-03-28T08:25:38Z
dc.date.issued	2017
dc.description.abstract	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	en_US
dc.identifier.isbn	978-1-5090-4063-6
dc.identifier.isbn	Electronic ISBN:978-1-5090-4062-9
dc.identifier.uri	https://ieeexplore.ieee.org/document/8054982
dc.identifier.uri	DOI: 10.1109/ISACV.2017.8054982
dc.identifier.uri	https://dspace.univ-boumerdes.dz/handle/123456789/6708
dc.language.iso	en	en_US
dc.publisher	IEEE	en_US
dc.relation.ispartofseries	2017 Intelligent Systems and Computer Vision (ISCV);
dc.subject	Abnormal behavior detection	en_US
dc.subject	Videos	en_US
dc.subject	Segmentation	en_US
dc.title	Strategy of detecting abnormal behaviors by fuzzy logic	en_US
dc.type	Article	en_US

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