author = "Alexandre, Eduardo Barreto and Chowdhury, Ananda Shankar and 
                         Falc{\~a}o, Alexandre Xavier and Miranda, Paulo A. Vechiatto",
          affiliation = "Institute of Mathematics and Statistics (IME), Dept. of Computer 
                         Science, University of S{\~a}o Paulo (USP) and Dept. of 
                         Electronics and Telecommunication Engineering, Jadavpur 
                         University, Kolkata, India and Institute of Computing, Dept. of 
                         Information Systems, University of Campinas and Institute of 
                         Mathematics and Statistics (IME), Dept. of Computer Science, 
                         University of S{\~a}o Paulo (USP)",
                title = "IFT-SLIC: A general framework for superpixel generation based on 
                         simple linear iterative clustering and image foresting transform",
            booktitle = "Proceedings...",
                 year = "2015",
               editor = "Papa, Jo{\~a}o Paulo and Sander, Pedro Vieira and Marroquim, 
                         Ricardo Guerra and Farrell, Ryan",
         organization = "Conference on Graphics, Patterns and Images, 28. (SIBGRAPI)",
            publisher = "IEEE Computer Society",
              address = "Los Alamitos",
             keywords = "Simple Linear Iterative Clustering, Image Foresting Transform, 
                         Superpixel, unsupervised segmentation.",
             abstract = "Image representation based on superpixels has become indispensable 
                         for improving efficiency in Computer Vision systems. Object 
                         recognition, segmentation, depth estimation, and body model 
                         estimation are some important problems where superpixels can be 
                         applied. However, superpixels can influence the efficacy of the 
                         system in positive or negative manner, depending on how well they 
                         respect the object boundaries in the image. In this paper, we 
                         improve superpixel generation by extending a popular algorithm - 
                         Simple Linear Iterative Clustering (SLIC) - to consider minimum 
                         path costs between pixel and cluster centers rather than their 
                         direct distances. This creates a new Image Foresting Transform 
                         (IFT) operator that naturally defines superpixels as regions of 
                         strongly connected pixels by choice of the most suitable path-cost 
                         function for a given application. Non-smooth connectivity 
                         functions are also explored in our IFT-SLIC approach leading to 
                         improved performance. Experimental results indicate better 
                         superpixel extraction using the proposed approach as compared to 
                         that of SLIC.",
  conference-location = "Salvador",
      conference-year = "Aug. 26-29, 2015",
             language = "en",
           targetfile = "00078.pdf",
        urlaccessdate = "2021, Dec. 04"