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@InProceedings{SouzaArPaCoNaKeGu:2013:HiViSe,
               author = "Souza, Kleber Jacques de and Araujo, Arnaldo de Albuquerque and 
                         Patrocinio Jr, Zenilton K. Gon{\c{c}}alves and Cousty, Jean and 
                         Najman, Laurent and Kenmochi, Yukiko and Guimaraes, Silvio Jamil 
                         F.",
          affiliation = "NPDI/DCC/UFMG and NPDI/DCC/UFMG and {VIPLAB/ICEI/PUC Minas} and 
                         Universit{\'e} Paris-Est, LIGM, ESIEE - UPEMLV - CNRS and 
                         Universit{\'e} Paris-Est, LIGM, ESIEE - UPEMLV - CNRS and 
                         Universit{\'e} Paris-Est, LIGM, ESIEE - UPEMLV - CNRS and 
                         {VIPLAB/ICEI/PUC Minas}",
                title = "Hierarchical video segmentation using an observation scale",
            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 = "Hierarchical video segmentation, Edge-weighted graph, Partition, 
                         Observation scale.",
             abstract = "Hierarchical video segmentation provides region-oriented 
                         scale-space, i.e., a set of video segmentations at different 
                         detail levels in which the segmentations at finer levels are 
                         nested with respect to those at coarser levels. Hierarchical 
                         methods have the interesting property of preserving spatial and 
                         neighboring information among segmented regions. Here, we 
                         transform the hierarchical video segmentation into a graph 
                         partitioning problem in which each part will correspond to one 
                         region of the video. Thus, we propose a new methodology for 
                         hierarchical video segmentation which computes a hierarchy of 
                         partitions by a reweighting of original graph in which a 
                         segmentation can be easily infered. The temporal coherence is 
                         given, only, by color information instead of more complex 
                         features. We provide an extensive comparative analysis, 
                         considering both quantitative and qualitative assessments showing 
                         efficiency, ease of use, and temporal coherence of our methods. 
                         According to our experiments, the hierarchy infered by our two 
                         methods, p-HOScale and cp-HOScale, produces good quantitative and 
                         qualitative results when applied to video segmentation. Moreover, 
                         unlike other tested methods, our methods are not influenced by the 
                         number of supervoxels to be computed, as shown in the experimental 
                         analysis, and present a low space cost.",
  conference-location = "Arequipa, Peru",
      conference-year = "Aug. 5-8, 2013",
             language = "en",
           targetfile = "SIBGRAPI2013VIDEOSEG.FINAL.IEEE.pdf",
        urlaccessdate = "2020, Dec. 05"
}


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