@InProceedings{AntonitschMussFigu:2020:StBeOr,
               author = "Antonitsch, Andr{\'e} da Silva and Musse, Soraia Raupp and 
                         Figueiredo, Luiz Henrique de",
          affiliation = "{Pontif{\'{\i}}cia Universidade Cat{\'o}lica do Rio Grande do 
                         Sul} and {Pontif{\'{\i}}cia Universidade Cat{\'o}lica do Rio 
                         Grande do Sul} and {Instituto de Matem{\'a}tica Pura e 
                         Aplicada}",
                title = "Towards a Legion of Virtual Humans: Steering Behaviors and Organic 
                         Visualization",
            booktitle = "Proceedings...",
                 year = "2020",
               editor = "Musse, Soraia Raupp and Cesar Junior, Roberto Marcondes and 
                         Pelechano, Nuria and Wang, Zhangyang (Atlas)",
         organization = "Conference on Graphics, Patterns and Images, 33. (SIBGRAPI)",
            publisher = "IEEE Computer Society",
              address = "Los Alamitos",
             keywords = "virtual human crowds, blobby models.",
             abstract = "Many studies have been done to control virtual humans and crowds. 
                         Navigation, split, merge, and collision avoidance are examples of 
                         what has been done in such areas when simulating crowds of 
                         individuals. This paper explores the macroscopic crowds' concept 
                         and seeks to solve two main issues: macroscopic crowd control and 
                         visualization. In particular, we are interested in providing 
                         steering behaviors applied to macroscopic models of crowds, in 
                         this case, called Legions of people, which are an abstraction for 
                         a vast amount of people. To provide the steering behaviors, we 
                         propose a multi-level control of such structures that can 
                         represent less or more people, in an emergent way. We also propose 
                         a new organic visualization of macroscopic and huge crowds based 
                         on blobby models.",
  conference-location = "Porto de Galinhas (virtual)",
      conference-year = "7-10 Nov. 2020",
                  doi = "10.1109/SIBGRAPI51738.2020.00013",
                  url = "http://dx.doi.org/10.1109/SIBGRAPI51738.2020.00013",
             language = "en",
                  ibi = "8JMKD3MGPEW34M/43AMDH8",
                  url = "http://urlib.net/ibi/8JMKD3MGPEW34M/43AMDH8",
           targetfile = "paper66.pdf",
        urlaccessdate = "2024, May 02"
}