@InProceedings{FavarettoDihlMuss:2016:DeCrFe,
               author = "Favaretto, Rodolfo Migon and Dihl, Leandro and Musse, Soraia 
                         Raupp",
          affiliation = "{Pontif{\'{\i}}cia Universidade Cat{\'o}lica do Rio Grande do 
                         Sul} and {Pontif{\'{\i}}cia Universidade Cat{\'o}lica do Rio 
                         Grande do Sul} and {Pontif{\'{\i}}cia Universidade Cat{\'o}lica 
                         do Rio Grande do Sul}",
                title = "Detecting crowd features in video sequences",
            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 = "image processing, fundamental diagrams, classification, crowd 
                         analysis.",
             abstract = "We propose a new methodology to detect social aspects of crowds in 
                         video sequences based on pedestrian features, which are obtained 
                         through image processing/computer vision techniques. The main idea 
                         is to apply and extend the concepts of Fundamental Diagram (FD) 
                         with more features, such as grouping and collectivity. Using crowd 
                         features we identify the crowd type and the main characteristics. 
                         In addition, we also investigated two further results: the visual 
                         assessment of people in real video sequences in order to detect 
                         crowd characteristics, and the usage of our method to detect 
                         similarity of crowds in videos.",
  conference-location = "S{\~a}o Jos{\'e} dos Campos, SP, Brazil",
      conference-year = "4-7 Oct. 2016",
                  doi = "10.1109/SIBGRAPI.2016.036",
                  url = "http://dx.doi.org/10.1109/SIBGRAPI.2016.036",
             language = "en",
                  ibi = "8JMKD3MGPAW/3M3PMKS",
                  url = "http://urlib.net/ibi/8JMKD3MGPAW/3M3PMKS",
           targetfile = "PID4344647.pdf",
        urlaccessdate = "2024, May 03"
}