author = "Le{\'o}n, Leissi Margarita Castañeda and Hirata Junior, Roberto",
          affiliation = "{Institute of Mathematics and Statistics} and {Institute of 
                         Mathematics and Statistics}",
                title = "Vehicle Detection using Mixture of Deformable Parts Models: Static 
                         and Dynamic Camera",
            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 = "Mixture of deformable part models, vehicle detection.",
             abstract = "Vehicle detection in video is an important problem in Computer 
                         Vision because of the potential applications in security, vehicle 
                         traffic, driving assistance and so on. In this work, we used 
                         Mixture of Deformable Part Models (MDPM) for vehicle detection in 
                         video sequences obtained from static and dynamic cameras. The MDPM 
                         method was originally proposed by Felzenszwalb et al in the realm 
                         of object detection in images. We tested this method in the realm 
                         of video sequences for vehicle detection. We designed a set of 
                         experiments that explore the number of components of the mixture 
                         and the number of parts model. We performed a comparison study of 
                         symmetric and asymmetric MDPMs for vehicle detection. Our findings 
                         show that not only the MDPM performed well in vehicle detection in 
                         video, but also the best number of components and parts model 
                         confirmed the number suggested in Felzenzwalb et al's paper. 
                         Finally, the results show some differences between the symmetric 
                         and asymmetric MDPMs in vehicle video detection considering 
                         different scenarios.",
  conference-location = "Ouro Preto",
      conference-year = "Aug. 22-25, 2012",
             language = "en",
           targetfile = "PID2451827.pdf",
        urlaccessdate = "2021, Jan. 28"