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@InProceedings{BerrielAguiSouzOliv:2015:PaFiLa,
               author = "Berriel, Rodrigo Ferreira and de Aguiar, Edilson and Souza Filho, 
                         Vanderlei Vieira de and Oliveira-Santos, Thiago",
          affiliation = "UFES and UFES and UFES and UFES",
                title = "A Particle Filter-based Lane Marker Tracking Approach using a 
                         Cubic Spline Model",
            booktitle = "Proceedings...",
                 year = "2015",
               editor = "Papa, Jo{\~a}o Paulo and Sander, Pedro Vieira and Marroquim, 
                         Ricardo Guerra and Farrell, Ryan",
         organization = "Conference on Graphics, Patterns and Images, 28. (SIBGRAPI)",
            publisher = "IEEE Computer Society",
              address = "Los Alamitos",
             keywords = "lane marker tracking, particle filter, cubic splines.",
             abstract = "In this paper we present a particle filter-based lane marker 
                         tracking approach using a cubic spline model. The system can 
                         detect the two main lane markers (i.e. lane strips) of marked 
                         roads from a monocular camera mounted on the top of a vehicle. 
                         Traditional lane marker detection and tracking systems have 
                         limitations to properly detect curved roads and to use temporal 
                         information to better estimate and track lane markers. The 
                         proposed system works on a temporal sequence of images. For each 
                         image, one at time, it applies a sequence of steps comprising an 
                         inverse perspective mapping to correct for perspective 
                         distortions, and a particle filter to smoothly track the lane 
                         markers along time. The output of the system is a lane marker 
                         generated by a cubic spline interpolation scheme to fit a wider 
                         range of lanes. Our system can run in real applications and it was 
                         validated with various road and traffic conditions. As a result, 
                         it achieves a high precision (98.13%) and a small error (0.0143 
                         meters).",
  conference-location = "Salvador",
      conference-year = "Aug. 26-29, 2015",
             language = "en",
           targetfile = "PID3755287.pdf",
        urlaccessdate = "2021, Nov. 28"
}


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