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@InProceedings{DutraCavaVidaMuss:2013:MuFiMo,
               author = "Dutra, Te{\'o}filo Bezerra and Cavalcante-Neto, Joaquim Bento and 
                         Vidal, Creto Augusto and Musse, Soraia Raupp",
          affiliation = "{Universidade Federal do Cear{\'a}} and {Universidade Federal do 
                         Cear{\'a}} and {Universidade Federal do Cear{\'a}} and 
                         {Pontif{\'{\i}}cia Universidade Cat{\'o}lica do Rio Grande do 
                         Sul}",
                title = "A multipotential field model for crowds with scalable behaviors",
            booktitle = "Proceedings...",
                 year = "2013",
               editor = "Boyer, Kim and Hirata, Nina and Nedel, Luciana and Silva, 
                         Claudio",
         organization = "Conference on Graphics, Patterns and Images, 26. (SIBGRAPI)",
            publisher = "IEEE Computer Society",
              address = "Los Alamitos",
             keywords = "Potential fields, reciprocal velocity obstacles, scalable 
                         behaviors, crowd simulation.",
             abstract = "Computer simulation of realistic crowd behavior has been the focus 
                         of active research for more than two decades now. In crowd 
                         simulation, there is usually a trade-off between performance and 
                         realistic crowd behavior. In this paper, we propose a model, based 
                         on potential fields, that enables the introduction of many 
                         behaviors in crowd simulations, while keeping good performance. 
                         The model uses multiple groups to guide agents to various 
                         different goals in the environment, and combines potential fields 
                         and reciprocal velocity obstacles (RVO) approaches, where the 
                         first sets the preferred velocities of the agents according to 
                         their current goals, whereas the second makes the agents avoid 
                         collisions. We used three scenarios to demonstrate the 
                         capabilities of our model for simulating crowds in which the 
                         agents present greater variety of behaviors in real-time without 
                         using a complex architecture.",
  conference-location = "Arequipa, Peru",
      conference-year = "Aug. 5-8, 2013",
             language = "en",
           targetfile = "PID2846543.pdf",
        urlaccessdate = "2020, Nov. 28"
}


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