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Title	A Comprehensive Review For Video Anomaly Detection On Videos
ID_Doc	908
Authors	Abbas Z.K.; Al-Ani A.A.
Year	2022
Published	Proceedings of the 2nd 2022 International Conference on Computer Science and Software Engineering, CSASE 2022
DOI	http://dx.doi.org/10.1109/CSASE51777.2022.9759598
Abstract	Video Surveillance Systems (VSS) are widely utilized in public and private areas to increase public safety, such as shopping malls, markets, banks, hospitals, educational institutions, streets, and smart cities. The accuracy and fast identification of video anomalies is usually the major goal of security applications. However, because of varying environmental factors, the complexities of human activity, the ambiguous nature of the anomaly, and the absence of appropriate datasets, detecting video anomalies is challenging. This paper surveys the last three years, a comprehensive study of detecting video anomalies, and the recently used dataset. Moreover, a comparison study on different approaches has been performed, which are used for anomalies detection. We have noticed that deep learning has outperformed other methods in this field. © 2022 IEEE.
Author Keywords	Anomaly detection; CNN; dataset; deep learning; Video surveillance

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