@InProceedings{PáduaPáduPereSous:2015:PaFiPr,
               author = "P{\'a}dua, Pedro Henrique Caetano de and P{\'a}dua, Fl{\'a}vio 
                         Luis Cardeal and Pereira, Marconi de Arruda and Sousa, Marco 
                         T{\'u}lio Diniz",
          affiliation = "{Centro Federal de Educa{\c{c}}{\~a}o Tecnol{\'o}gica de Minas 
                         Gerais} and {Centro Federal de Educa{\c{c}}{\~a}o 
                         Tecnol{\'o}gica de Minas Gerais} and {Universidade Federal de 
                         S{\~a}o Jo{\~a}o del-Rei} and {Centro Federal de 
                         Educa{\c{c}}{\~a}o Tecnol{\'o}gica de Minas Gerais}",
                title = "Particle filter-based predictive tracking of futsal players from a 
                         single stationary camera",
            booktitle = "Proceedings...",
                 year = "2015",
               editor = "Papa, Jo{\~a}o Paulo and Sander, Pedro Vieira and Marroquim, 
                         Ricardo Guerra and Farrell, Ryan",
         organization = "Conference on Graphics, Patterns and Images, 28. (SIBGRAPI)",
            publisher = "IEEE Computer Society",
              address = "Los Alamitos",
             keywords = "player tracking, particle filter, futsal, tactical and physical 
                         analyses.",
             abstract = "In this paper we study the use of computer vision techniques for 
                         visual tracking of futsal players. In the sports field, player 
                         tracking is an important task, as it can provide an estimate of 
                         the position of the athlete in a given time and thus compute 
                         his/her trajectories. This information can be used by coaches and 
                         sport professionals on tactical and physical analyses. We use 
                         adaptive background subtraction and blob analysis to detect 
                         players, as well as particle filters to predict their positions 
                         and track them using data from a single stationary camera. 
                         Experimental results show that our approach is capable to track 
                         players and compute their trajectories over time with errors below 
                         20 cm, thus demonstrating a high potential to be used in a wide 
                         range of futsal match analyses.",
  conference-location = "Salvador, BA, Brazil",
      conference-year = "26-29 Aug. 2015",
                  doi = "10.1109/SIBGRAPI.2015.10",
                  url = "http://dx.doi.org/10.1109/SIBGRAPI.2015.10",
             language = "en",
                  ibi = "8JMKD3MGPBW34M/3JKUKML",
                  url = "http://urlib.net/ibi/8JMKD3MGPBW34M/3JKUKML",
           targetfile = "PID3755085.pdf",
        urlaccessdate = "2024, May 05"
}