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Predicting Future Crowd Motion Including Event Treatment

Part of the Lecture Notes in Computer Science book series (LNAI,volume 10498)


Crowd simulation has become an important area, mainly in entertainment and security applications. In particular, this area has been explored in safety systems to evaluate environments in terms of people comfort and security. In general, the evaluation involves the execution of one or more simulations in order to provide statistical information about the crowd behavior in a certain environment. Real-time applications can also be desirable, for instance in order to estimate the crowd behavior in a near future knowing the current crowd state, aiming to anticipate a potential problem and prevent it. This paper presents a model to estimate crowd behaviors in a future time, presenting a good compromise between accuracy and running time. It also presents a new error measure to compare two crowds based on local density.

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  1. de Almeida, I.R., Cassol, V.J., Badler, N.I., Musse, S.R., Jung, C.R.: Detection of global and local motion changes in human crowds. IEEE Transactions on Circuits and Systems for Video Technology 27(3), 603–612 (2017)

    CrossRef  Google Scholar 

  2. Bianco, C.M.D., Braun, A., Musse, S.R., Jung, C., Badler, N.: Fast-forwarding crowd simulations. In: Traum, D., Swartout, W., Khooshabeh, P., Kopp, S., Scherer, S., Leuski, A. (eds.) IVA 2016. LNCS, vol. 10011, pp. 208–217. Springer, Cham (2016). doi:10.1007/978-3-319-47665-0_19

    CrossRef  Google Scholar 

  3. Dal Bianco, C.M., Braun, A., Brasil, J., Musse, S.R.: Preserving the motion features in nonavoiding collision crowds. Comput. Entertain 15(3), 2:1–2:15 (2017)

    Google Scholar 

  4. Lerner, A., Chrysanthou, Y., Shamir, A., Cohen-Or, D.: Data driven evaluation of crowds. In: Egges, A., Geraerts, R., Overmars, M. (eds.) MIG 2009. LNCS, vol. 5884, pp. 75–83. Springer, Heidelberg (2009). doi:10.1007/978-3-642-10347-6_7

    CrossRef  Google Scholar 

  5. Van Toll, W.G., Cook, A.F., Geraerts, R.: Real-time density-based crowd simulation. Comput. Animat. Virtual Worlds 23(1), 59–69 (2012)

    Google Scholar 

  6. Yi, S., Li, H., Wang, X.: Pedestrian travel time estimation in crowded scenes. In: 2015 IEEE International Conference on Computer Vision (ICCV), pp. 3137–3145, December 2015

    Google Scholar 

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Correspondence to Soraia Raupp Musse .

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Dal Bianco, C.M., Musse, S.R., Braun, A., Caetani, R.P., Jung, C., Badler, N. (2017). Predicting Future Crowd Motion Including Event Treatment. In: Beskow, J., Peters, C., Castellano, G., O'Sullivan, C., Leite, I., Kopp, S. (eds) Intelligent Virtual Agents. IVA 2017. Lecture Notes in Computer Science(), vol 10498. Springer, Cham.

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-67400-1

  • Online ISBN: 978-3-319-67401-8

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