TY  - CONF
T1  - ADABeV: Automatic Detection of Abnormal Behavior in Video-surveillance
A1  - Charara, Nour
A1  - Jarkass, Iman
A1  - Maria, Sokhn
A1  - Mugellini, Elena
A1  - Abou Khaled, Omar
Y1  - 2012
T2  - International Conference on Image, Signal and Vision Computing
CY  - Oslo, Norway
KW  - Behavior recognition
KW  - Crowded scene
KW  - data fusion
KW  - Pattern Recognition
KW  - Video-surveillance
N2  - 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.
ER  -