A video anomaly detection framework based on multi-scale dynamic prototype unit

Wanlin Liu; Zhenlong Du; Xiaoli Li

doi:10.1117/12.3037165

22 October 2024 A video anomaly detection framework based on multi-scale dynamic prototype unit

Wanlin Liu, Zhenlong Du, Xiaoli Li

Proceedings Volume 13274, Sixteenth International Conference on Digital Image Processing (ICDIP 2024); 132740A (2024) https://doi.org/10.1117/12.3037165
Event: Sixteenth International Conference on Digital Image Processing (ICDIP 2024), 2024, Haikou, HI, China

Abstract

Many existing works fail to make full use of temporal information and ignore the diversity of normal behaviors in video anomaly detection tasks. In this paper, we propose a multi-scale dynamic prototype unit based video anomaly detection method. Some works proposed an autoencoder anomaly detection model based on dynamic prototype unit (DPU), which effectively improves the performance of anomaly detection, but ignores the importance of different levels of features for normal event modeling. Therefore, this paper proposes an anomaly detection model based on multi-scale dynamic prototype unit (DPU), which uses memory units to establish connections between encoder and decoder. Normal patterns at different scales are learned. In addition, based on the Temporal Shift technique, the temporal information of video can be mined more effectively to generate future video frames. Experimental results on UCSD Ped2, CUHK Avenue and ShanghaiTech datasets show that the proposed method is superior to the current mainstream video anomaly detection methods while meeting the real-time requirements.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Wanlin Liu, Zhenlong Du, and Xiaoli Li "A video anomaly detection framework based on multi-scale dynamic prototype unit", Proc. SPIE 13274, Sixteenth International Conference on Digital Image Processing (ICDIP 2024), 132740A (22 October 2024); https://doi.org/10.1117/12.3037165

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KEYWORDS

Video

Education and training

Prototyping

Video surveillance

Video coding

Performance modeling

Data modeling

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