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Neural Processing Letters
Erschienen in: Neural Processing Letters 2/2022

19.01.2022

Fast Anomaly Detection Based on 3D Integral Images

verfasst von: Shifeng Li, Yan Cheng, Yunfeng Liu, Yuqiang Yang

Erschienen in: Neural Processing Letters | Ausgabe 2/2022

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Abstract

In this paper, we propose a method to detect abnormal events from videos based on the integral image under Bayesian framework. In our implementation, we consider a regular cube in the videos as one event. Each event is represented as a motion histogram which can be calculated fast from our proposed 3D integral images. Furthermore, we estimate the anomaly probability under the Bayesian framework, where we estimate the prior knowledge from the motion magnitudes and calculate the likelihood based on our maximum histogram templates. Experiments on the public datasets show that our method can effectively and efficiently detect abnormal events in complex scenes.
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Fußnoten
1
We keep two significant digits because that the compared methods from different references also have the same significant digits.
 
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Metadaten
Titel
Fast Anomaly Detection Based on 3D Integral Images
verfasst von
Shifeng Li
Yan Cheng
Yunfeng Liu
Yuqiang Yang
Publikationsdatum
19.01.2022
Verlag
Springer US
Erschienen in
Neural Processing Letters / Ausgabe 2/2022
Print ISSN: 1370-4621
Elektronische ISSN: 1573-773X
DOI
https://doi.org/10.1007/s11063-021-10691-8

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