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Crowd gathering and commotion detection based on the stillness and motion model

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Abstract

The abnormal event detection becomes an important topic recently. This paper presents a method to detect the crowd gathering, as well as the commotion event after the crowd gathering. The proposed stillness model and the motion model are based on the improved background subtraction and the optical flow feature. We construct the long-term stillness level by the break bucket model and clustering the instantaneous stillness level. Then the crowd gathering event is decided by the threshold with the long-term stillness level. Furthermore, the motion model is applied for detecting the commotion event after the crowd gathering. In the experiment, we used the dataset of PET2009. The proposed method is verified by the experiment with 97% accuracy.

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Acknowledgements

The author wishes to acknowledge the help of Prof. Derlis O. Gregor in giving helpful comments on the part of the work. We want to thank anonymous reviewers and the editor for their comments.

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  1. Department of Electronic and Computer Engineering, National Taiwan University of Science and Technology (NTUST), No.43, Keelung Rd., Sec.4, Da’an Dist., Taipei City, 10607, Taiwan (R.O.C.)

    Deng-Shun Yang, Chun-Yu Liu, Wei-Hao Liao & Shanq-Jang Ruan

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  1. Deng-Shun Yang
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  2. Chun-Yu Liu
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  3. Wei-Hao Liao
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  4. Shanq-Jang Ruan
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Correspondence to Shanq-Jang Ruan.

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Yang, DS., Liu, CY., Liao, WH. et al. Crowd gathering and commotion detection based on the stillness and motion model. Multimed Tools Appl 79, 19435–19449 (2020). https://doi.org/10.1007/s11042-020-08827-4

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  • DOI: https://doi.org/10.1007/s11042-020-08827-4

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