@InProceedings{LourençoSilvFern:2019:LeApTr,
               author = "Louren{\c{c}}o, V{\'{\i}}tor N. and Silva, Gabriela G. and 
                         Fernandes, Leandro A. F.",
          affiliation = "{Universidade Federal Fluminense} and {Universidade Federal 
                         Fluminense} and {Universidade Federal Fluminense}",
                title = "Hierarchy-of-Visual-Words: a Learning-based Approach for Trademark 
                         Image Retrieval",
            booktitle = "Proceedings...",
                 year = "2019",
               editor = "Oliveira, Luciano Rebou{\c{c}}as de and Sarder, Pinaki and Lage, 
                         Marcos and Sadlo, Filip",
         organization = "Conference on Graphics, Patterns and Images, 32. (SIBGRAPI)",
            publisher = "IEEE Computer Society",
              address = "Los Alamitos",
             keywords = "Trademark image retrieval, visual feature extraction and matching, 
                         learning-based approach.",
             abstract = "In this paper, we present the Hierarchy-of-Visual-Words (HoVW), a 
                         novel trademark image retrieval (TIR) method that decomposes 
                         images into simpler geometric shapes and defines a descriptor for 
                         binary trademark image representation by encoding the hierarchical 
                         arrangement of component shapes. The proposed hierarchical 
                         organization of visual data stores each component shape as a 
                         visual word. It is capable of representing the geometry of 
                         individual elements and the topology of the trademark image, 
                         making the descriptor robust against linear as well as to some 
                         level of nonlinear transformation. Experiments show that HoVW 
                         outperforms previous TIR methods on the MPEG-7 CE-1 and MPEG-7 
                         CE-2 image databases.",
  conference-location = "Rio de Janeiro, RJ, Brazil",
      conference-year = "28-31 Oct. 2019",
                  doi = "10.1109/SIBGRAPI.2019.00037",
                  url = "http://dx.doi.org/10.1109/SIBGRAPI.2019.00037",
             language = "en",
                  ibi = "8JMKD3MGPEW34M/3U2CTAL",
                  url = "http://urlib.net/ibi/8JMKD3MGPEW34M/3U2CTAL",
           targetfile = "35-cr.pdf",
        urlaccessdate = "2024, Apr. 28"
}