@InProceedings{SouzaAlmMolJrGui:2016:GaGeVi,
               author = "Souza, Renato Augusto de and Almeida, Raquel Pereira de and 
                         Moldovan, Arghir-Nicolae and Jr. , Zenilton Kleber G. do 
                         Patrocinio and Guimaraes, Silvio Jamil F.",
          affiliation = "{Audio-Visual Information Proc. Lab. (VIPLAB) - Computer Science 
                         Department -- ICEI -- PUC Minas} and {Audio-Visual Information 
                         Proc. Lab. (VIPLAB) - Computer Science Department -- ICEI -- PUC 
                         Minas} and School of Computing, National College of Ireland, 
                         Dublin, Ireland and {Audio-Visual Information Proc. Lab. (VIPLAB) 
                         - Computer Science Department -- ICEI -- PUC Minas} and 
                         {Audio-Visual Information Proc. Lab. (VIPLAB) - Computer Science 
                         Department -- ICEI -- PUC Minas}",
                title = "Gameplay genre video classification by using mid-level video 
                         representation",
            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 = "Gameplay videos, gameplay genre video classification, mid-level 
                         video representation, BossaNova video descriptor.",
             abstract = "As video gameplay recording and streaming is becoming very popular 
                         on the Internet, there is an increasing need for automatic 
                         classification solutions to help service providers with indexing 
                         the huge amount of content and users with finding relevant 
                         content. The automatic classification of gameplay videos into 
                         specific genres is not a trivial task due to their high content 
                         diversity. This paper address the problem of classifying video 
                         gameplay recordings into different genres by using mid-level video 
                         representation based on the BossaNova descriptor. The paper also 
                         proposes a public dataset called GameGenre containing 700 gameplay 
                         videos groped into 7 genres. The results from experimental testing 
                         show up to 89% classification accuracy when the gameplay videos 
                         are described by BossaNova descriptor using BinBoost as low-level 
                         image descriptor.",
  conference-location = "S{\~a}o Jos{\'e} dos Campos, SP, Brazil",
      conference-year = "4-7 Oct. 2016",
                  doi = "10.1109/SIBGRAPI.2016.034",
                  url = "http://dx.doi.org/10.1109/SIBGRAPI.2016.034",
             language = "en",
                  ibi = "8JMKD3MGPAW/3M5KBQB",
                  url = "http://urlib.net/ibi/8JMKD3MGPAW/3M5KBQB",
           targetfile = "PID4373567.pdf",
        urlaccessdate = "2024, May 03"
}