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@InProceedings{DoriniGold:2006:NoFeUn,
               author = "Dorini, Leyza Elmeri Baldo and Goldenstein, Siome Klein",
          affiliation = "{Unicamp - Universidade Estadual de Campinas} and {Unicamp - 
                         Universidade Estadual de Campinas}",
                title = "Unscented KLT: nonlinear feature and uncertainty tracking",
            booktitle = "Proceedings...",
                 year = "2006",
               editor = "Oliveira Neto, Manuel Menezes de and Carceroni, Rodrigo Lima",
         organization = "Brazilian Symposium on Computer Graphics and Image Processing, 19. 
                         (SIBGRAPI)",
            publisher = "IEEE Computer Society",
              address = "Los Alamitos",
             keywords = "feature tracking, uncertainty tracking, outlier rejection.",
             abstract = "Accurate feature tracking is the foundation of several high level 
                         tasks, such as 3D reconstruction and motion analysis. Although 
                         there are many feature tracking algorithms, most of them do not 
                         maintain information about the error of the data being tracked. In 
                         this paper, we propose a new generic framework that uses the 
                         Scaled Unscented Transform (SUT) to augment arbitrary feature 
                         tracking algorithms, by introducing Gaussian Random Variables 
                         (GRV) for the representation of features' locations uncertainties. 
                         Here, we apply the framework to the well-understood 
                         Kanade-Lucas-Tomasi (KLT) feature tracker, giving birth to what we 
                         call Unscented KLT (UKLT). It tracks probabilistic confidences and 
                         better rejects errors, all on-line, and leads to more robust 
                         computer vision applications. We also validade the experiments 
                         with a bundle adjustment procedure, using real and synthetic 
                         sequences.",
  conference-location = "Manaus",
      conference-year = "8-11 Oct. 2006",
             language = "en",
           targetfile = "dorini-Uklt.pdf",
        urlaccessdate = "2020, Nov. 25"
}


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