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Unsupervised video surveillance
Year: 2010 Keywords: Behavior analysis, long time observations, unsupervised learning
Authors: Francesca Odone, Nicoletta Noceti  
Editor: Reinhard Koch and Fay Huang Volume: 6468
Book title: Proc. of ACCV 2010
Series: Lecture Notes in Computer Science Pages: 84-93
Month: November
This paper addresses the problem of automatically learning common behaviors from long time observations of a scene of interest, with the purpose of classifying actions and, possibly, detecting anomalies. Unsupervised learning is used as an e ective way to extract information from the scene with a very limited intervention of the user. The method we propose is rather general, but ts very naturally to a videosurveillance scenario, where the same environment is observed for a long time, usually from a distance. The experimental analysis is based on thousands of dynamic events acquired by three-weeks observations of a single-camera video-surveillance system installed in our department.
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