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App. Res. of Comp. Accepted Paper
Vol. 42, 2025 No. 6

Unsupervised video anomaly detection method based on hyperbolic space

Qi Meilin
Wu Yuanyuan
Zhang Hang
Lin Wenlong
Chengdu University of Technology, College of Computer & Network Security, Chengdu, Chengdu 610059, China
DOI: 10.19734/j.issn.1001-3695.2024.08.0371

Abstract

In the field of video anomaly detection, anomalous events often demonstrate temporal continuity and similarity. Existing unsupervised methods typically segment videos into multiple clips and randomly select subsets for training, disrupting the continuity of anomalous events and causing the loss of critical spatiotemporal information. Additionally, current Euclidean space-based methods encounter limitations in embedding space dimensionality, making it difficult to effectively capture the latent geometric hierarchy of video data. To address these issues, this paper introduces a novel unsupervised video anomaly detection method based on hyperbolic space. It designs a Spatiotemporal Feature Construction (STFC) module to extract temporal correlations and feature similarities among video segments, embedding these into Lorentz and Poincaré ball hyperbolic spaces to learn richer video representations that more effectively distinguish normal from abnormal events. Experiments show that this method achieves AUC scores of 93.26% and 77.55% on the Shanghai Tech and UCF-Crime datasets, respectively, outperforming existing unsupervised video anomaly detection methods. These results confirm the advantage of hyperbolic space in capturing the latent geometric hierarchy of video data and highlight its potential in enhancing anomaly detection capabilities.

Foundation Support

成都理工大学2023年中青年骨干教师发展资助计划(10912-JXGG2023-06470)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2024.08.0371
Publish at: Application Research of Computers Accepted Paper, Vol. 42, 2025 No. 6

Publish History

[2025-03-06] Accepted Paper

Cite This Article

漆美林, 吴媛媛, 张航, 等. 基于双曲空间的无监督视频异常检测方法 [J]. 计算机应用研究, 2025, 42 (6). (2025-03-10). https://doi.org/10.19734/j.issn.1001-3695.2024.08.0371. (Qi Meilin, Wu Yuanyuan, Zhang Hang, et al. Unsupervised video anomaly detection method based on hyperbolic space [J]. Application Research of Computers, 2025, 42 (6). (2025-03-10). https://doi.org/10.19734/j.issn.1001-3695.2024.08.0371. )

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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