Technology of Graphic & Image
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App. Res. of Comp. Printed Article
Vol. 41, 2024 No. 1
306-313,320

Lightweight video abnormal event detection method for edge devices

Li Nanjun1,2
Li Shuang3
Li Tuo1,2
Zou Xiaofeng1,2
Wang Changhong1,2
1. Shandong Yunhai Guochuang Cloud Computing Equipment Industry Innovation Co. , Ltd. , Jinan 250013, China
2. State Key Laboratory of High-end Server & Storage Technology, Jinan 250013, China
3. Qilu University of Technology(Shandong Academy of Sciences), Jinan 250353, China
DOI: 10.19734/j.issn.1001-3695.2023.04.0225

Abstract

Existing CNN-based video anomaly detection methods improve the accuracy continuously, which are faced with issues such as complex architecture, large parameters and lengthy training. Therefore, the hardware computing power requirements of them are high, which makes it difficult to adapt to edge devices with limited computing resources like UAVs. To this end, this paper proposed a lightweight abnormal event detection method for edge devices. Firstly, the method extracted gradient cuboids and optical flow cuboids from video sequence as appearance and motion feature representation. Secondly, the method designed a modified PCANet network to obtain high-level block-wise histogram features of gradient cuboids. Then, the method calculated the appearance anomaly score of each block based on histogram feature distribution, and calculated the motion anomaly score based on the accumulation of optical flow amplitudes of internal pixels. Finally, the method fused the appearance and motion anomaly scores to identify anomalous blocks, achieving appearance and motion abnormal events detection and localization simultaneously. The frame-level AUC of proposed method reached 86.7% on UCSD Ped1 dataset and 94.9% on UCSD Ped2 dataset, which were superior to other methods and the parameters were much smaller. Experimental results show that the method achieves better anomaly detection performance under low computational power requirements, making the balance between detection precision and computing resources, which is suitable for low-power edge devices.

Foundation Support

山东省自然科学基金资助项目(ZR2023QF050)
国家自然科学基金资助项目(62203242)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2023.04.0225
Publish at: Application Research of Computers Printed Article, Vol. 41, 2024 No. 1
Section: Technology of Graphic & Image
Pages: 306-313,320
Serial Number: 1001-3695(2024)01-049-0306-08

Publish History

[2023-08-14] Accepted Paper
[2024-01-05] Printed Article

Cite This Article

李南君, 李爽, 李拓, 等. 面向边缘端设备的轻量化视频异常事件检测方法 [J]. 计算机应用研究, 2024, 41 (1): 306-313,320. (Li Nanjun, Li Shuang, Li Tuo, et al. Lightweight video abnormal event detection method for edge devices [J]. Application Research of Computers, 2024, 41 (1): 306-313,320. )

About the Journal

  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

Application Research of Computers has many high-level readers and authors, and its readers are mainly senior and middle-level researchers and engineers engaged in the field of computer science, as well as teachers and students majoring in computer science and related majors in colleges and universities. Over the years, the total citation frequency and Web download rate of Application Research of Computers have been ranked among the top of similar academic journals in this discipline, and the academic papers published are highly popular among the readers for their novelty, academics, foresight, orientation and practicality.

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