@InProceedings{PessoaSchwSant:2016:LoViFe,
               author = "Pessoa, Ramon Figueiredo and Schwartz, William Robson and dos 
                         Santos, Jefersson Alex",
          affiliation = "{Universidade Federal de Minas Gerais (UFMG)} and {Universidade 
                         Federal de Minas Gerais (UFMG)} and {Universidade Federal de Minas 
                         Gerais (UFMG)}",
                title = "Low-cost visual feature representations for image retrieval",
            booktitle = "Proceedings...",
                 year = "2016",
               editor = "Aliaga, Daniel G. and Davis, Larry S. and Farias, Ricardo C. and 
                         Fernandes, Leandro A. F. and Gibson, Stuart J. and Giraldi, Gilson 
                         A. and Gois, Jo{\~a}o Paulo and Maciel, Anderson and Menotti, 
                         David and Miranda, Paulo A. V. and Musse, Soraia and Namikawa, 
                         Laercio and Pamplona, Mauricio and Papa, Jo{\~a}o Paulo and 
                         Santos, Jefersson dos and Schwartz, William Robson and Thomaz, 
                         Carlos E.",
         organization = "Conference on Graphics, Patterns and Images, 29. (SIBGRAPI)",
            publisher = "Sociedade Brasileira de Computa{\c{c}}{\~a}o",
              address = "Porto Alegre",
             keywords = "image search, global descriptors, binary descriptors, bag of 
                         visual words, spatial bag of visual words.",
             abstract = "This work addressed two research issues in order to investigate 
                         and to propose effective solutions for image retrieval on mobile 
                         devices: 1) low-cost representation for mobile image search and 2) 
                         spatial visual feature extraction. First, we test twenty mid-level 
                         representations of binary descriptors, ten color descriptors, five 
                         texture descriptors and two shape descriptors in ten datasets, 
                         considering the trade-off configuration regarding effectiveness, 
                         efficiency, and compactness of visual features. Finally, we 
                         propose two approaches of spatial bags of visual words called 
                         BOBGrid (spatial Bag Of BIC Grid) and BOBSlic (spatial Bag Of 
                         Slic) and compare them with our baselines. In statistical 
                         analyzes, BOBGrid and BOBSlic achieved processing results and 
                         performed better than our baselines WSA and BOSSANova.",
  conference-location = "S{\~a}o Jos{\'e} dos Campos, SP, Brazil",
      conference-year = "4-7 Oct. 2016",
             language = "en",
                  ibi = "8JMKD3MGPAW/3M9LQ3E",
                  url = "http://urlib.net/ibi/8JMKD3MGPAW/3M9LQ3E",
           targetfile = "RFP_Sibgrapi2016WTD.pdf",
        urlaccessdate = "2024, Apr. 28"
}