@InProceedings{FonsecaPaiv:2021:SyViAn,
               author = "Fonseca, Cibele Mara and Paiva, Jose Gustavo S.",
          affiliation = "{Federal University of Uberlandia } and {Federal University of 
                         Uberlandia}",
                title = "A System for Visual Analysis of Objects Behavior in Surveillance 
                         Videos",
            booktitle = "Proceedings...",
                 year = "2021",
               editor = "Paiva, Afonso and Menotti, David and Baranoski, Gladimir V. G. and 
                         Proen{\c{c}}a, Hugo Pedro and Junior, Antonio Lopes Apolinario 
                         and Papa, Jo{\~a}o Paulo and Pagliosa, Paulo and dos Santos, 
                         Thiago Oliveira and e S{\'a}, Asla Medeiros and da Silveira, 
                         Thiago Lopes Trugillo and Brazil, Emilio Vital and Ponti, Moacir 
                         A. and Fernandes, Leandro A. F. and Avila, Sandra",
         organization = "Conference on Graphics, Patterns and Images, 34. (SIBGRAPI)",
            publisher = "IEEE Computer Society",
              address = "Los Alamitos",
             keywords = "objects behavior, visualization, visual analytics, surveillance 
                         video.",
             abstract = "Closed-circuit television (CCTV) surveillance systems are employed 
                         in different scenarios to prevent a variety of threats, producing 
                         a large volume of video footage. Several surveillance tasks 
                         consist of detecting/tracking moving objects in the scene to 
                         analyze their behavior and comprehend their role in events that 
                         occur in the video. Such analysis is unfeasible if manually 
                         performed, due to the large volume of long duration videos, as 
                         well as due to intrinsic human limitations, which may compromise 
                         the perception of multiple strategic events. Most of smart 
                         surveillance approaches designed for moving objects analysis focus 
                         only on the detection/tracking process, providing a limited 
                         comprehension of objects behavior, and rely on automatic 
                         procedures with no/few user interaction, which may hamper the 
                         comprehension of the produced results. Visual analytics techniques 
                         may be useful to highlight behavior patterns, improving the 
                         comprehension of how the objects contribute to the occurrence of 
                         observed events in the video. In this work, we propose a video 
                         surveillance visual analysis system for identification/exploration 
                         of objects behavior and their relationship with events occurrence. 
                         We introduce the Appearance Bars layout to perform a temporal 
                         analysis of each object presence in the scene, highlighting the 
                         involved dynamics and spatial distribution, as well as its 
                         interaction with other objects. Coordinated with other support 
                         layouts, these bars represent multiple aspects of the objects 
                         behavior during video extent. We demonstrate the utility of our 
                         system in surveillance scenarios that shows different aspects of 
                         objects behavior, which we relate to events that occur in the 
                         videos.",
  conference-location = "Gramado, RS, Brazil (virtual)",
      conference-year = "18-22 Oct. 2021",
                  doi = "10.1109/SIBGRAPI54419.2021.00032",
                  url = "http://dx.doi.org/10.1109/SIBGRAPI54419.2021.00032",
             language = "en",
                  ibi = "8JMKD3MGPEW34M/45CHQS2",
                  url = "http://urlib.net/ibi/8JMKD3MGPEW34M/45CHQS2",
           targetfile = "15.pdf",
        urlaccessdate = "2024, May 06"
}