Abstract
Fluid methods have been introduced to analysis of crowd movements in videos recent years. Among these methods, Lattice Boltzmann model has been widely used as a quite convenient tool. Moreover, the Lattice Boltzmann model describes crowd movement as fluid, and the particles of the fluid flow randomly. Therefore, it is very difficult for the model to simulate the crowds purpose drive. In this study, a lattice Boltzmann based model added with a traction force term, which represents the crowds purpose drive toward the exit, is proposed. The model input is optical flow velocity field. Less error in the velocity fields computing and the capability in forecasting the crowd state is obtained.
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Tao, Y., Liu, P., Zhao, W., Tang, X. (2014). Forecasting Crowd State in Video by an Improved Lattice Boltzmann Model. In: Loo, C.K., Yap, K.S., Wong, K.W., Beng Jin, A.T., Huang, K. (eds) Neural Information Processing. ICONIP 2014. Lecture Notes in Computer Science, vol 8836. Springer, Cham. https://doi.org/10.1007/978-3-319-12643-2_7
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DOI: https://doi.org/10.1007/978-3-319-12643-2_7
Publisher Name: Springer, Cham
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