Abnormal behaviour detection method for video surveillance applications
R.A. Shatalin, V.R. Fidelman, P.E. Ovchinnikov

 

Lobachevsky State University of Nizhny Novgorod, Nizhny Novgorod, Russia

Full text of article: Russian language.

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Abstract:
In this paper, we propose novel method for abnormal behavior detection in the video surveillance. The method constructs a normal behavior model using training samples, which makes possible application in a wide range of conditions and scenes. The method was tested in controlled and real conditions. The result shows that the method can be used to detect abnormal behavior in simple and crowded scenes.

Keywords:
video analysis, surveillance, anomaly detection, crowded scene, principal component analysis.

Citation:
Shatalin RA, Fidelman VR, Ovchinnikov PE. Abnormal behavior detection method for video surveillance applications. Computer Optics 2017; 41(1): 37-45. DOI: 10.18287/2412-6179-2017-41-1-37-45.

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