@InProceedings{ChoqueluqueRomanCáma:2020:ViDeLo,
               author = "Choqueluque Roman, David Gabriel and C{\'a}mara Ch{\'a}vez, 
                         Guillermo",
          affiliation = "Department of Computer Science, Universidad Cat{\'o}lica San 
                         Pablo, Arequipa, Per{\'u} and Department of Computer Science, 
                         Federal University of Ouro Preto, Ouro Preto, Brazil",
                title = "Violence Detection and Localization in Surveillance Video",
            booktitle = "Proceedings...",
                 year = "2020",
               editor = "Musse, Soraia Raupp and Cesar Junior, Roberto Marcondes and 
                         Pelechano, Nuria and Wang, Zhangyang (Atlas)",
         organization = "Conference on Graphics, Patterns and Images, 33. (SIBGRAPI)",
            publisher = "IEEE Computer Society",
              address = "Los Alamitos",
             keywords = "Violence detection, violence localization, video surveillance, 
                         dynamic images, video summarization, saliency detection.",
             abstract = "Automatic violence detection in video surveillance is crucial for 
                         social and personal security. Due to the massive video data 
                         produced by surveillance cameras installed in different 
                         environments like airports, trains, stadiums, schools, etc., 
                         traditional video monitoring by humans operators becomes 
                         inefficient. In this context, develop systems capable of detect 
                         automatically violent actions is a challenging task. This study 
                         describes a method to detect and localize violent acts in video 
                         surveillance using dynamic images, CNN's, and weakly supervised 
                         localization methods. Experimental results demonstrate the 
                         effectiveness of our approach when applied to three public 
                         benchmark datasets: Hockey Fight, Violent Flows, and 
                         UCFCrime2Local.",
  conference-location = "Porto de Galinhas (virtual)",
      conference-year = "7-10 Nov. 2020",
                  doi = "10.1109/SIBGRAPI51738.2020.00041",
                  url = "http://dx.doi.org/10.1109/SIBGRAPI51738.2020.00041",
             language = "en",
                  ibi = "8JMKD3MGPEW34M/43BDNEB",
                  url = "http://urlib.net/ibi/8JMKD3MGPEW34M/43BDNEB",
           targetfile = "107.pdf",
        urlaccessdate = "2024, May 04"
}