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ADABeV: Automatic Detection of Abnormal Behavior in Video-surveillance
Type of publication: Inproceedings
Citation:
Year: 2012
Month: August
Location: Oslo, Norway
Organization: International Conference on Image, Signal and Vision Computing
Abstract: Intelligent Video-Surveillance (IVS) systems are being more and more popular in security applications. The analysis and recognition of abnormal behaviours in a video sequence has gradually drawn the attention in the field of IVS, since it allows filtering out a large number of useless information, which guarantees the high efficiency in the security protection, and save a lot of human and material resources. We present in this paper ADABeV, an intelligent video-surveillance framework for event recognition in crowded scene to detect the abnormal human behaviour. This framework is attended to be able to achieve real-time alarming, reducing the lags in traditional monitoring systems. This architecture proposal addresses four main challenges: behaviour understanding in crowded scenes, hard lighting conditions, multiple input kinds of sensors and contextual-based adaptability to recognize the active context of the scene.
Keywords: Behavior recognition, Crowded scene, data fusion, Pattern Recognition, Video-surveillance
Authors Charara, Nour
Jarkass, Iman
Maria, Sokhn
Mugellini, Elena
Abou Khaled, Omar
Added by: []
Total mark: 0
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