@InProceedings{CostaBald:2013:MeAuId,
               author = "Costa, George Henrique Rangel and Baldo, Fabiano",
          affiliation = "{Universidade do Estado de Santa Catarina (UDESC)} and 
                         {Universidade do Estado de Santa Catarina (UDESC)}",
                title = "A method to automatically identify road centerlines from 
                         georeferenced smartphone data",
            booktitle = "Anais...",
                 year = "2013",
               editor = "Andrade, Pedro Ribeiro and Santanch{\`e}, Andr{\'e}",
                pages = "12",
         organization = "Simp{\'o}sio Brasileiro de Geoinform{\'a}tica, 14. (GEOINFO).",
            publisher = "Instituto Nacional de Pesquisas Espaciais (INPE)",
              address = "S{\~a}o Jos{\'e} dos Campos",
             abstract = "Digital road maps have gained fundamental role in populations 
                         daily life, so they need to be accurate and up-to-date. A viable 
                         solution is to generate maps by processing GPS data. However, one 
                         of the most challenging tasks regarding this approach is how to 
                         extract road centerlines from the cloud of georeferenced GPS 
                         points. The literature presents various methods that do it, but 
                         none have been found that is prepared for the continuous update of 
                         the map and refinement of its roads accuracy. In this context, the 
                         objective of this work is to propose a method to identify road 
                         centerlines using an evolutive algorithm in order to generate and 
                         update road maps. This work uses as source of data GPS traces 
                         collected by smartphones. Although suitable to obtain a large 
                         amount of georeferenced data, these devices bring the additional 
                         problem of identifying the transport vehicle used along each 
                         trace. Preliminary results indicate that the methods performance 
                         is satisfactory, with an average variation of 2.95 meters in 
                         relation to satellite images.",
  conference-location = "Campos do Jord{\~a}o",
      conference-year = "24-27 nov. 2013",
                 issn = "2179-4820",
             language = "en",
                  ibi = "8JMKD3MGP8W/3FCF4JP",
                  url = "http://urlib.net/ibi/8JMKD3MGP8W/3FCF4JP",
           targetfile = "paper8.pdf",
        urlaccessdate = "23 maio 2024"
}