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Computer Optics, 2017, Volume 41, Issue 1, Pages 37–45
DOI: https://doi.org/10.18287/2412-6179-2017-41-1-37-45 (Mi co356) 		 
This article is cited in 11 scientific papers (total in 11 papers)

IMAGE PROCESSING, PATTERN RECOGNITION

Abnormal behavior 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 PDF (410 kB) Citations (11)
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DOI: https://doi.org/10.18287/2412-6179-2017-41-1-37-45
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.
Received: 18.07.2016
Accepted: 31.12.2017
Document Type: Article
Language: Russian
Citation: R. A. Shatalin, V. R. Fidelman, P. E. Ovchinnikov, “Abnormal behavior detection method for video surveillance applications”, Computer Optics, 41:1 (2017), 37–45
Citation in format AMSBIB
\Bibitem{ShaFidOvc17}
\by R.~A.~Shatalin, V.~R.~Fidelman, P.~E.~Ovchinnikov
\paper Abnormal behavior detection method for video surveillance applications
\jour Computer Optics
\yr 2017
\vol 41
\issue 1
\pages 37--45
\mathnet{http://mi.mathnet.ru/co356}
\crossref{https://doi.org/10.18287/2412-6179-2017-41-1-37-45}
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    • This publication is cited in the following 11 articles:
    Citing articles in Google Scholar: Russian citations, English citations
    Related articles in Google Scholar: Russian articles, English articles
    		Computer Optics
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    References:38
     
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