@InProceedings{SantosMori:2008:PeDeUn,
               author = "Santos, Thiago Teixeira and Morimoto, Carlos Hitoshi",
          affiliation = "{Institute of Mathematics and Statistics - University of S{\~a}o 
                         Paulo} and {Institute of Mathematics and Statistics - University 
                         of S{\~a}o Paulo}",
                title = "People detection under occlusion in multiple camera views",
            booktitle = "Proceedings...",
                 year = "2008",
               editor = "Jung, Cl{\'a}udio Rosito and Walter, Marcelo",
         organization = "Brazilian Symposium on Computer Graphics and Image Processing, 21. 
                         (SIBGRAPI)",
            publisher = "IEEE Computer Society",
              address = "Los Alamitos",
             keywords = "detection, surveillance, multiple view, video.",
             abstract = "This paper proposes a method to locate people on a reference plane 
                         using multiple cameras. Previous works rely on people trajectories 
                         and color models to solve occlusion. This new approach solves 
                         people detection under occlusion by accumulating evidence from 
                         multiple views instantaneously and does not rely on previous 
                         segmentation of individuals in foreground data or any tracking 
                         information. First, foreground data from one view, segmented using 
                         background subtraction, is projected onto the ground plane or 
                         reference image. The projected foreground of a second view 
                         overlaps the first projected foreground only on the points where 
                         the foreground intersects the ground plane. Thus, by accumulating 
                         the evidence from multiple views, people can be located by 
                         detecting local maxima on the accumulated reference image. 
                         Experimental results using publicly available data from PETS06 [9] 
                         show that the method robustly locates people in very challenging 
                         situations with occlusion in most of the views. The locations on 
                         the ground plane can further be used for segmentation and tracking 
                         on each camera view under severe occlusion.",
  conference-location = "Campo Grande, MS, Brazil",
      conference-year = "12-15 Oct. 2008",
                  doi = "10.1109/SIBGRAPI.2008.25",
                  url = "http://dx.doi.org/10.1109/SIBGRAPI.2008.25",
             language = "en",
                  ibi = "6qtX3pFwXQZG2LgkFdY/UMHj2",
                  url = "http://urlib.net/ibi/6qtX3pFwXQZG2LgkFdY/UMHj2",
           targetfile = "santos-PeopleDetectionOcclusion.pdf",
        urlaccessdate = "2024, Apr. 29"
}