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This article is cited in 5 scientific papers (total in 5 papers)
NUMERICAL METHODS AND DATA ANALYSIS
Incremental learning of an abnormal behavior detection algorithm based on principal components
R. A. Shatalin, V. R. Fidelman, P. E. Ovchinnikov Lobachevsky State University of Nizhny Novgorod, Nizny Novgorod, Russia
Abstract:
In this paper, we propose an incremental learning scheme for the abnormal behavior detection algorithm based on principal component. The results obtained on a UCSD dataset and our experimental videos at a different number of training samples show that error rates are similar to conventional learning. Moreover, the proposed scheme allows the incremental learning time to be significantly reduced in comparison with a method based on matrix eigendecomposition.
Keywords:
incremental learning, video analysis, anomaly detection, principal component analysis.
Received: 27.08.2019 Accepted: 10.12.2019
Citation:
R. A. Shatalin, V. R. Fidelman, P. E. Ovchinnikov, “Incremental learning of an abnormal behavior detection algorithm based on principal components”, Computer Optics, 44:3 (2020), 476–481
Linking options:
https://www.mathnet.ru/eng/co811 https://www.mathnet.ru/eng/co/v44/i3/p476
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Abstract page: | 152 | Full-text PDF : | 46 | References: | 19 |
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