@InProceedings{MacêdoJúniorGoisVelh:2009:HeInIm,
               author = "Mac{\^e}do J{\'u}nior, Ives Jos{\'e} de Albuquerque and Gois, 
                         Jo{\~a}o Paulo and Velho, Luiz Carlos Pacheco Rodrigues",
          affiliation = "{IMPA - Instituto Nacional de Matem{\'a}tica Pura e Aplicada} and 
                         {Universidade Federal do ABC} and {IMPA - Instituto Nacional de 
                         Matem{\'a}tica Pura e Aplicada}",
                title = "Hermite Interpolation of Implicit Surfaces with Radial Basis 
                         Functions",
            booktitle = "Proceedings...",
                 year = "2009",
               editor = "Nonato, Luis Gustavo and Scharcanski, Jacob",
         organization = "Brazilian Symposium on Computer Graphics and Image Processing, 22. 
                         (SIBGRAPI)",
            publisher = "IEEE Computer Society",
              address = "Los Alamitos",
             keywords = "implicit surfaces, Hermite data, radial basis functions, 
                         Hermite-Birkhoff interpolation, scattered data approximation, 
                         geometric modeling, surface reconstruction.",
             abstract = "We present the Hermite radial basis function (HRBF) implicits 
                         method to compute a global implicit function which interpolates 
                         scattered multivariate Hermite data (unstructured points and their 
                         corresponding normals). Differently from previous radial basis 
                         functions (RBF) approaches, HRBF implicits do not depend on offset 
                         points to ensure existence and uniqueness of its interpolant. 
                         Intrinsic properties of this method allow the computation of 
                         implicit surfaces rich in details, with irregularly spaced points 
                         even in the presence of close sheets. Comparisons to previous 
                         works show the effectiveness of our approach. Further, the 
                         theoretical background of HRBF implicits relies on results from 
                         generalized interpolation theory with RBFs, making possible 
                         powerful new variants of this method and establishing connections 
                         with previous efforts based on statistical learning theory.",
  conference-location = "Rio de Janeiro, RJ, Brazil",
      conference-year = "11-14 Oct. 2009",
                  doi = "10.1109/SIBGRAPI.2009.11",
                  url = "http://dx.doi.org/10.1109/SIBGRAPI.2009.11",
             language = "en",
                  ibi = "8JMKD3MGPBW4/35S5B7P",
                  url = "http://urlib.net/ibi/8JMKD3MGPBW4/35S5B7P",
           targetfile = "macedo-HRBFImplicits.pdf",
        urlaccessdate = "2024, May 03"
}