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@InProceedings{CabreraAvilaOrtiGonį:2018:ToMeCo,
               author = "Cabrera Avila, Elizabeth Viviana and Ortiz Fern{\'a}ndez, Luis 
                         Enrique and Gon{\c{c}}alves Garcia, Luiz Marcos.",
          affiliation = "{Universidad Federal do Rio Grande do Norte} and {Universidad 
                         Federal do Rio Grande do Norte} and {Universidad Federal do Rio 
                         Grande do Norte}",
                title = "Towards a metric for computing similarity ofrestricted non-rigid 
                         objects in real time",
            booktitle = "Proceedings...",
                 year = "2018",
               editor = "Ross, Arun and Gastal, Eduardo S. L. and Jorge, Joaquim A. and 
                         Queiroz, Ricardo L. de and Minetto, Rodrigo and Sarkar, Sudeep and 
                         Papa, Jo{\~a}o Paulo and Oliveira, Manuel M. and Arbel{\'a}ez, 
                         Pablo and Mery, Domingo and Oliveira, Maria Cristina Ferreira de 
                         and Spina, Thiago Vallin and Mendes, Caroline Mazetto and Costa, 
                         Henrique S{\'e}rgio Gutierrez and Mejail, Marta Estela and Geus, 
                         Klaus de and Scheer, Sergio",
         organization = "Conference on Graphics, Patterns and Images, 31. (SIBGRAPI)",
            publisher = "Sociedade Brasileira de Computa{\c{c}}{\~a}o",
              address = "Porto Alegre",
             keywords = "similarity, non-rigid objects, restricted deformation, point 
                         clouds, Mahalanobis distance, Hausdorf distance, real time.",
             abstract = "We propose an approach towards measuring the similarity of 
                         restricted deformable objects using three-dimensional point clouds 
                         of them. Basically, given the point clouds of the object in the 
                         ideal and deformed postures, object part labeling is performed 
                         based on RGB to find a first segmentation of the object cloud in 
                         parts. Then two methods are tested for measuring similarity of 
                         each partial clouds set, with verification of their precision and 
                         time: the computation of Mahalanobis distances and of the 
                         Hausdorff distances of the point clouds, the last after 
                         registration and alignment of them. Experimental results show a 
                         faster execution time of the Mahalanobis metric, in despite of its 
                         lower precision in similarity estimation. Several applications in 
                         computer graphics and virtual reality can rely on such result in 
                         order to determine levels of deformation of articulated or 
                         restricted deformable objects.",
  conference-location = "Foz do Igua{\c{c}}u, PR, Brazil",
      conference-year = "Oct. 29 - Nov. 1, 2018",
             language = "en",
                  ibi = "8JMKD3MGPAW/3S4DK2H",
                  url = "http://urlib.net/rep/8JMKD3MGPAW/3S4DK2H",
           targetfile = "paper_tesis_ready.pdf",
        urlaccessdate = "2020, Dec. 02"
}


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