@InProceedings{SousaVelhFern:2017:ReTiPl,
               author = "Sousa, Eduardo Vera and Velho, Luiz and Fernandes, Leandro Augusto 
                         Frata",
          affiliation = "{Universidade Federal Fluminense} and {Instituto Nacional de 
                         Matem{\'a}tica Pura e Aplicada} and {Universidade Federal 
                         Fluminense}",
                title = "D-KHT: Real time plane detection in depth images",
            booktitle = "Proceedings...",
                 year = "2017",
               editor = "Torchelsen, Rafael Piccin and Nascimento, Erickson Rangel do and 
                         Panozzo, Daniele and Liu, Zicheng and Farias, Myl{\`e}ne and 
                         Viera, Thales and Sacht, Leonardo and Ferreira, Nivan and Comba, 
                         Jo{\~a}o Luiz Dihl and Hirata, Nina and Schiavon Porto, Marcelo 
                         and Vital, Creto and Pagot, Christian Azambuja and Petronetto, 
                         Fabiano and Clua, Esteban and Cardeal, Fl{\'a}vio",
         organization = "Conference on Graphics, Patterns and Images, 30. (SIBGRAPI)",
            publisher = "Sociedade Brasileira de Computa{\c{c}}{\~a}o",
              address = "Porto Alegre",
             keywords = "depth images, pattern recognition, Hough transform, real time.",
             abstract = "The automatic detection of geometric primitives (e.g. planes, 
                         spheres, etc.) in depth images provides the basis for solving many 
                         computer vision problems. The applications range from robotics to 
                         augmented reality. For plane detection, the quality of previous 
                         techniques is strongly related to the amount of noise and 
                         discontinuities or, in the case of unorganized point clouds, 
                         depends on complex structures to organize the points, besides 
                         having high computational cost. In this paper, we present a 
                         real-time deterministic algorithm for plane detection in depth 
                         images. By using an implicit quadtree to cluster approximately 
                         coplanar points in the 2.5-D space associated with an efficient 
                         Hough Transform voting scheme and a hill climbing strategy to find 
                         local maxima, we are able to reach real-time detection. 
                         Experiments show that our approach works well even in presence of 
                         noise, partial occlusion, and discontinuities.",
  conference-location = "Niter{\'o}i, RJ, Brazil",
      conference-year = "17-20 Oct. 2017",
             language = "en",
                  ibi = "8JMKD3MGPAW/3PJ62EE",
                  url = "http://urlib.net/ibi/8JMKD3MGPAW/3PJ62EE",
           targetfile = "CReady___WTD___SIBGRAPI_2017.pdf",
        urlaccessdate = "2024, May 02"
}