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KUMBH MELA: a case study for dense crowd counting and modeling

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Abstract

Dense crowd counting and modeling at different gatherings has ignited a new flame in the visual surveillance research community. There is a high possibility of mishappenings in the form of stampede, mob fighting at these gatherings and the administration is helpless in these scenarios. There is a requirement of analyzing the crowd to prevent these dangerous situations. The proposed work is a case study of Kumbh Mela which models the crowd counting in densely populated images. In the proposed work, the orthographic projection of the crowd is captured using a camera attached to a drone, to reduce the effect of occlusion and scaling which, otherwise, may get introduce during image acquisition process. The captured data is fed to a Convolutional Neural Network for training the model to count head of persons present in the frame. The results obtained from the trained model are validated using geometry and imaging techniques. The proposed model has achieved a mean-absolute-error of 94.3 and a mean-squared-error of 104.6 which seems to outperform the existing state-of-the-art models with respect to the reported performance parameters. The proposed model can be used as a viable solution in applications related to modeling the crowd behavior.

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Notes

  1. http://worldpopulationreview.com/countries/india-population/

  2. Record 120 million take dip as Maha Kumbh fest ends. Khaleej Times. 12 March 2013.

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Acknowledgements

This work has been supported by the Kumbh Mela Police, Kumbh Mela, Prayagraj, Uttar Pradesh. We would like to specially acknowledge, Mr. K.P. Singh, DIG, Kumbh Mela, Prayagraj for allowing us to collect video data through drone cameras. We are also thankful to the reviewers for their constructive suggestions.

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Authors and Affiliations

  1. Engineering & RnD services, HCL Technologies Ltd., Noida, India

    Anurag Pandey

  2. Motilal Nehru National Institute of Technology Allahabad, Prayagraj, 211004, India

    Mayank Pandey, Navjot Singh & Abha Trivedi

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  1. Anurag Pandey
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  2. Mayank Pandey
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  3. Navjot Singh
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Correspondence to Navjot Singh.

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Pandey, A., Pandey, M., Singh, N. et al. KUMBH MELA: a case study for dense crowd counting and modeling. Multimed Tools Appl 79, 17837–17858 (2020). https://doi.org/10.1007/s11042-020-08754-4

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