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@InProceedings{DutraSouAlvSchOli:2013:RePeBa,
               author = "Dutra, Cristianne Rodrigues Santos and Souza, Tiago and Alves, 
                         Raul and Schwartz, William Robson and Oliveira, Luciano",
          affiliation = "{Universidade Federal de Minas Gerais} and {Federal University of 
                         Bahia} and {Federal University of Bahia} and {Universidade Federal 
                         de Minas Gerais} and {Federal University of Bahia}",
                title = "Re-identifying People based on Indexing Structure and Manifold 
                         Appearance Modeling",
            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 = "Person re-identification, bag-of-features, predominance filter, 
                         inverted lists, mean Riemann covariance.",
             abstract = "The role of person re-identification has increased in the recent 
                         years due to the large camera networks employed in surveillance 
                         systems. The goal in this case is to identify individuals that 
                         have been previously identified in a different camera. Even though 
                         several approaches have been proposed, there are still challenges 
                         to be addressed, such as illumination changes, pose variation, low 
                         acquisition quality, appearance modeling and the management of the 
                         large number of subjects being monitored by the surveillance 
                         system. The present work tackles the last problem by developing an 
                         indexing structure based on inverted lists and a predominance 
                         filter descriptor with the aim of ranking candidates with more 
                         probability of being the target search person. With this initial 
                         ranking, a more strong classification is done by means of a mean 
                         Riemann covariance method, which is based on a appearance 
                         strategy. Experimental results show that the proposed indexing 
                         structure returns an accurate short-list containing the most 
                         likely candidates, and that manifold appearance model is able to 
                         set the correct candidate among the initial ranks in the 
                         identification process. The proposed method is comparable to other 
                         state-of-the-art approaches.",
  conference-location = "Arequipa, Peru",
      conference-year = "Aug. 5-8, 2013",
             language = "en",
           targetfile = "paper_CameraReady.pdf",
        urlaccessdate = "2020, Nov. 26"
}


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