@InProceedings{NogueiraTozz:1998:GeAuMa,
               author = "Nogueira, Fernando Marques de Almeida and Tozzi, Cl{\'e}sio 
                         Luis",
                title = "Gera{\c{c}}{\~a}o Autom{\'a}tica de Mapas de Disparidade em 
                         Vis{\~a}o Est{\'e}reo",
            booktitle = "Proceedings...",
                 year = "1998",
               editor = "Costa, L. da F and Camara, G.",
         organization = "International Symposium on Computer Graphics, Image Processing and 
                         Vision, 11. (SIBGRAPI)",
            publisher = "Sociedade Brasileira de Computa{\c{c}}{\~a}o",
              address = "Porto Alegre",
                 note = "The conference was held in Rio de Janeiro, RJ, Brazil, from 
                         October 20 to 23.",
             keywords = "shape from stereo, disparity, matching, gradient",
             abstract = "Tridimensional information of a scene can be obtained using the 
                         technique named {"}shape from stereo{"}. The major difficulty of 
                         this technique is the automatic determination of correspondence 
                         between images (matching points). The stereo matching solution can 
                         be obtained from area-based matching and/or feature-based matching 
                         and represented as a disparity map. Most of the contemporaneous 
                         algorithms found in the literature employ feature-based matching 
                         techniques for the stereo matching. This class of matching 
                         produces a sparse disparity map, which is further interpolated in 
                         a smooth dense disparity map that does not represent correctly the 
                         scene abrupt variations in depth. An approach for stereo matching 
                         that results in dense and non-smooth disparity map is presented in 
                         this work. In a first step, a smooth and dense disparity map is 
                         obtained by interpolation of the disparity values obtained from 
                         feature-based matching. In a second step, this map is iteratively 
                         adjusted, using area-based matching techniques, and a dense 
                         disparity map that supports non-smooth surfaces is obtained. The 
                         main idea used in this approach is based on biologic evidence of 
                         disparity gradient that is present in the living beings vision 
                         systems. The methodology was applied to synthetic and real images 
                         and the obtained results show the coherence between the 3-D 
                         geometry of the scene and the disparity map generated.",
  conference-location = "Rio de Janeiro, RJ, Brazil",
      conference-year = "20-23 Oct. 1998",
         organisation = "SBC - Sociedade Brasileira de Computa{\c{c}}{\~a}o",
                  ibi = "83LX3pFwXQZeBBx/fLfdi",
                  url = "http://urlib.net/ibi/83LX3pFwXQZeBBx/fLfdi",
           targetfile = "slp017.pdf",
        urlaccessdate = "2024, May 03"
}