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Research on variational optical flow method for rockfall monitoring

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Abstract

Rockfall is a global mountain disaster problem, which has the characteristics of wide distribution, strong randomness, and inconspicuousness. The contacted monitoring method is difficult to deploy. Simultaneously, the non-contact detection is easily affected by complex environments and generally has less robustness. This paper presents a rockfall monitoring technology based on machine vision. First, a high-resolution industrial camera continuously acquires images of the monitoring area. Then, we perform a series of operations on the landslide rockfall images, including image preprocessing, image optical flow algorithm preprocessing to identify the features of the rockfall. Finally, a dynamic target detection experiment is carried out to verify the feasibility of the image optical flow algorithm. Experiments of rockfall monitoring verify the effectiveness and generalization abilities of the algorithm. From the results: (1) The features of the image data in this paper are clear, and the recognition range covers the whole visual field. (2) The technology can capture the motion characteristics of landslide rockfall in different scenes. (3) The processing efficiency of the algorithm can reach 10 frames per second. Thus, this technology can be used in a monitoring system for rockfall.

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Acknowledgements

The authors sincerely thank the editors and reviewers for their constructive comments, which will greatly help improve the quality of this paper.

Funding

The work was supported in part by the State Key Laboratory of Geohazard Prevention and Geoenvironment Protection Independent Research Project under Grant SKLGP2022Z011; in part by the Creative Research Groups of the Natural Science Foundation of Sichuan under Grants 2023NSFSC1984; in part by the Research Project of Chunhui Plan, Ministry of Education.

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Authors and Affiliations

  1. State Key Laboratory of Geohazard Prevention and Geoenvironment Protection, Chengdu University of Technology, Chengdu, 610059, Sichuan, China

    Hui Chen

  2. Geomathematics Key Laboratory of Sichuan Province, Chengdu University of Technology, Chengdu, 610059, Sichuan, China

    Hui Chen, Lu Zhang, Ying Zhang & Juan Liu

  3. College of Mathematics and Physics, Chengdu University of Technology, Chengdu, 610059, Sichuan, China

    Hui Chen, Lu Zhang, Ying Zhang & Juan Liu

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  1. Hui Chen
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Contributions

All authors contributed to the research of this paper. Hui Chen contributed to conceptualization, resources, methodology, and funding acquisition. Lu Zhang contributed to methodology, investigation, data acquisition and experiment. Ying Zhang contributed to formal analysis, visualization, data acquisition and experiment. Juan Liu contributed to validation, data acquisition and experiment.

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Correspondence to Hui Chen.

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Chen, H., Zhang, L., Zhang, Y. et al. Research on variational optical flow method for rockfall monitoring. SIViP (2024). https://doi.org/10.1007/s11760-024-03187-0

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