@InProceedings{DuartePenaAlme:2016:BaGeVi,
               author = "Duarte, Leonardo Assuane and Penatti, Ot{\'a}vio A. B. and 
                         Almeida, Jurandy",
          affiliation = "{Federal University of S{\~a}o Paulo} and {Advanced Technologies 
                         SAMSUNG Research Institute} and {Federal University of S{\~a}o 
                         Paulo}",
                title = "Bag of Genres for Video 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 = "IEEE Computer Society´s Conference Publishing Services",
              address = "Los Alamitos",
             keywords = "video retrieval, video representation, visual dictionaries, 
                         semantics.",
             abstract = "Often, videos are composed of multiple concepts or even genres. 
                         For instance, news videos may contain sports, action, nature, etc. 
                         Therefore, encoding the distribution of such concepts/genres in a 
                         compact and effective representation is a challenging task. In 
                         this sense, we propose the Bag of Genres representation, which is 
                         based on a visual dictionary defined by a genre classifier. Each 
                         visual word corresponds to a region in the classification space. 
                         The Bag of Genres video vector contains a summary of the 
                         activations of each genre in the video content. We evaluate the 
                         proposed method for video genre retrieval using the dataset of 
                         MediaEval Tagging Task of 2012 and for video event retrieval using 
                         the EVVE dataset. Results show that the proposed method achieves 
                         results comparable or superior to state-of-the-art methods, with 
                         the advantage of providing a much more compact representation than 
                         existing features.",
  conference-location = "S{\~a}o Jos{\'e} dos Campos, SP, Brazil",
      conference-year = "4-7 Oct. 2016",
                  doi = "10.1109/SIBGRAPI.2016.043",
                  url = "http://dx.doi.org/10.1109/SIBGRAPI.2016.043",
             language = "en",
                  ibi = "8JMKD3MGPAW/3M5JLEP",
                  url = "http://urlib.net/ibi/8JMKD3MGPAW/3M5JLEP",
           targetfile = "main.pdf",
        urlaccessdate = "2024, May 03"
}