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@InProceedings{RauberFalcSpinReze:2013:InSeIm,
               author = "Rauber, Paulo Eduardo and Falc{\~a}o, Alexandre Xavier and Spina, 
                         Thiago Vallin and Rezende, Pedro Jussieu de",
          affiliation = "{University of Campinas (UNICAMP)} and {University of Campinas 
                         (UNICAMP)} and {University of Campinas (UNICAMP)} and {University 
                         of Campinas (UNICAMP)}",
                title = "Interactive segmentation by image foresting transform on 
                         superpixel graphs",
            booktitle = "Proceedings...",
                 year = "2013",
               editor = "Boyer, Kim and Hirata, Nina and Nedel, Luciana and Silva, 
                         Claudio",
         organization = "Conference on Graphics, Patterns and Images, 26. (SIBGRAPI)",
            publisher = "IEEE Computer Society",
              address = "Los Alamitos",
             keywords = "graph-based image segmentation, image foresting transform, robot 
                         users, interactive segmentation.",
             abstract = "There are many scenarios in which user interaction is essential 
                         for effective image segmentation. In this paper, we present a new 
                         interactive segmentation method based on the Image Foresting 
                         Transform (IFT). The method oversegments the input image, creates 
                         a graph based on these segments (superpixels), receives markers 
                         (labels) drawn by the user on some superpixels and organizes a 
                         competition to label every pixel in the image. Our method has 
                         several interesting properties: it is effective, efficient, 
                         capable of segmenting multiple objects in almost linear time on 
                         the number of superpixels, readily extendable through previously 
                         published techniques, and benefits from domain-specific feature 
                         extraction. We also present a comparison with another technique 
                         based on the IFT, which can be seen as its pixel-based 
                         counterpart. Another contribution of this paper is the description 
                         of automatic (robot) users. Given a ground truth image, these 
                         robots simulate interactive segmentation by trained and untrained 
                         users, reducing the costs and biases involved in comparing 
                         segmentation techniques.",
  conference-location = "Arequipa, Peru",
      conference-year = "Aug. 5-8, 2013",
             language = "en",
           targetfile = "article_checked.pdf",
        urlaccessdate = "2020, Nov. 29"
}


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