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@InProceedings{MoraisGoldFerrRoch:2012:AuTrIn,
               author = "Morais, Erikson Freitas de and Goldenstein, Siome and Ferreira, 
                         Anselmo and Rocha, Anderson",
          affiliation = "IC-UNICAMP and IC-UNICAMP and IC-UNICAMP and IC-UNICAMP",
                title = "Automatic tracking of indoor soccer players using videos from 
                         multiple cameras",
            booktitle = "Proceedings...",
                 year = "2012",
               editor = "Freitas, Carla Maria Dal Sasso and Sarkar, Sudeep and Scopigno, 
                         Roberto and Silva, Luciano",
         organization = "Conference on Graphics, Patterns and Images, 25. (SIBGRAPI)",
            publisher = "IEEE Computer Society",
              address = "Los Alamitos",
             keywords = "Tracking, Soccer, Particle Filter, Data Fusion.",
             abstract = "Indoor soccer has been of tactical and scientific interest, with 
                         applications dedicated to analyze tactical and physiological 
                         factors and also physical training. In both cases, the analysis is 
                         based on player tracking, done with human supervision. This paper 
                         presents an automatic tracking method which shows the trajectories 
                         of indoor soccer players during the game and saving skilled labor 
                         during the process. For this, we use a predictive filter to model 
                         the motion and the observation of multiple stationary cameras, 
                         strategically positioned around the court. We associate a particle 
                         filter to a robust probabilistic observation model with the 
                         measurement in court coordinates. The observation model proposed 
                         is based on data fusion across multiple camera coordinates and 
                         projected onto the court plane, creating a multimodal and 
                         bidirectional probability function, which represents the potential 
                         localization of players in the court plane. The probability 
                         function uses an appearance model to observe player's location, 
                         distinguishing very close players and yielding good weights in the 
                         observation model. The experimental results show tracking errors 
                         below 70 centimeters in most cases and indicate the potential of 
                         the method to help sports teams.",
  conference-location = "Ouro Preto",
      conference-year = "Aug. 22-25, 2012",
             language = "en",
           targetfile = "sibgrapi-2012-camera-ready-paper-102126.pdf",
        urlaccessdate = "2021, Jan. 24"
}


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