@InProceedings{JungJacqSoldMuss:2006:DeUnMo,
               author = "Jung, Claudio Rosito and Jacques Jr, Julio C. S. and Soldera, John 
                         and Musse, Soraia Raupp",
          affiliation = "{PIPCA - Graduate School on Applied Computing - Universidade do 
                         Vale do Rio dos Sinos} and {PIPCA - Graduate School on Applied 
                         Computing - Universidade do Vale do Rio dos Sinos} and {PIPCA - 
                         Graduate School on Applied Computing - Universidade do Vale do Rio 
                         dos Sinos} and {PIPCA - Graduate School on Applied Computing - 
                         Universidade do Vale do Rio dos Sinos}",
                title = "Detection of Unusual Motion Using Computer Vision",
            booktitle = "Proceedings...",
                 year = "2006",
               editor = "Oliveira Neto, Manuel Menezes de and Carceroni, Rodrigo Lima",
         organization = "Brazilian Symposium on Computer Graphics and Image Processing, 19. 
                         (SIBGRAPI)",
            publisher = "IEEE Computer Society",
              address = "Los Alamitos",
             keywords = "computer vision, human motion analysis, object tracking.",
             abstract = "In this paper, we propose different criteria for detecting unusual 
                         motion in surveillance cameras. Initially, a certain environment 
                         is observed within a time interval, and captured trajectories are 
                         used as examples of usual trajectories. These trajectories are 
                         used to build a Spatial Occupancy Map (SpOM, which is introduced 
                         in this paper) of the observed people, as well as main flow 
                         directions. In the test period, each new trajectory is classified 
                         as normal or unusual with respect to spatial occupancy and 
                         trajectory consistency. The spatial occupancy criterion considers 
                         the relation of space occupancy between the new tracked trajectory 
                         and the observed period. The trajectory consistency criterion 
                         considers the agreement of the new trajectory with the main flows 
                         extracted in the training period. Experimental results showed that 
                         these criteria can be used as an automatic pre-screening of 
                         suspect motion in surveillance applications.",
  conference-location = "Manaus, AM, Brazil",
      conference-year = "8-11 Oct. 2006",
                  doi = "10.1109/SIBGRAPI.2006.11",
                  url = "http://dx.doi.org/10.1109/SIBGRAPI.2006.11",
             language = "en",
                  ibi = "6qtX3pFwXQZG2LgkFdY/Mfvry",
                  url = "http://urlib.net/ibi/6qtX3pFwXQZG2LgkFdY/Mfvry",
           targetfile = "jungc-unusual.pdf",
        urlaccessdate = "2024, May 04"
}