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Review
. 2023 Aug 26;23(17):7442.
doi: 10.3390/s23177442.

Online Video Anomaly Detection

Yuxing Zhang  1 , Jinchen Song  1 , Yuehan Jiang  1 , Hongjun Li  1   2
Affiliations
Review

Online Video Anomaly Detection

Yuxing Zhang et al. Sensors (Basel). .

Abstract

With the popularity of video surveillance technology, people are paying more and more attention to how to detect abnormal states or events in videos in time. Therefore, real-time, automatic and accurate detection of abnormal events has become the main goal of video-based surveillance systems. To achieve this goal, many researchers have conducted in-depth research on online video anomaly detection. This paper presents the background of the research in this field and briefly explains the research methods of offline video anomaly detection. Then, we sort out and classify the research methods of online video anomaly detection and expound on the basic ideas and characteristics of each method. In addition, we summarize the datasets commonly used in online video anomaly detection and compare and analyze the performance of the current mainstream algorithms according to the evaluation criteria of each dataset. Finally, we summarize the future trends in the field of online video anomaly detection.

Keywords: online video anomaly detection; real time; video surveillance.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Anomaly detection in video surveillance scenes. (a) A truck moving on the footpath (UCSD Dataset). (b) Pedestrian walking on a lawn (UCSD Dataset). (c) A person throwing an object (Avenue). (d) A person carrying a suspicious bag (Avenue). (e) Incorrect parking of vehicle (MDVD). (f) People fighting (MDVD). (g) A person catching a bag (ShanghaiTech). (h) A vehicle moving on the footpath (ShanghaiTech) [5].
Figure 2
Figure 2
Video anomaly detection methods.
See this image and copyright information in PMC

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