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@InProceedings{MacźdoFarLimKelAlb:2011:CaSt3D,
               author = "Mac{\^e}do, Samuel Victor Medeiros de and Farias, Thiago Souto 
                         Maior Cordeiro de and Lima, Juliane Cristina Botelho de Oliveira 
                         and Kelner, Judith and Albuquerque, Eduardo",
          affiliation = "UFPE and UFPE and UFPE and UFPE and UFG",
                title = "Towards a Standalone Methodology for Robust Algorithms Evaluation: 
                         A Case Study in 3D Reconstruction",
            booktitle = "Proceedings...",
                 year = "2011",
               editor = "Lewiner, Thomas and Torres, Ricardo",
         organization = "Conference on Graphics, Patterns and Images, 24. (SIBGRAPI)",
            publisher = "IEEE Computer Society Conference Publishing Services",
              address = "Los Alamitos",
             keywords = "robust algorithms, standalone methodology, statistical tests, 
                         hypothesis testing.",
             abstract = "In the field of 3D reconstruction there are two main challenging 
                         tasks that require careful consideration, namely, feature 
                         detection and matching. The corresponding automatic process 
                         introduces noise resulting from the image capture and spurious 
                         features matching. A number of robust algorithms for hypothesis 
                         evaluation have been suggested; they would deal with these 
                         limitations by removing outliers. Most of these works are merely 
                         comparisons to previous algorithms and lack any standalone 
                         evaluation. This paper attempts to fill this gap by introducing a 
                         novel and robust statistical methodology. It has the advantage of 
                         evaluating related algorithms using non-dimensional metrics for 
                         fixed and continuous intervals. In addition, the proposed 
                         methodology is validated using a proof of concept scenario based 
                         on the 3D pose estimation phase in the 3D reconstruction pipeline. 
                         The obtained results are very promising and emphasize the 
                         methodology's generic nature, clearing the way for its application 
                         in a multitude of scenarios, such as computer vision and 3D 
                         reconstruction.",
  conference-location = "Macei{\'o}",
      conference-year = "Aug. 28 - 31, 2011",
             language = "en",
           targetfile = "example.pdf",
        urlaccessdate = "2019, Dec. 09"
}


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