TY - JOUR AU - Miller, Nicholas AU - Swart, David M. AU - Mishra, Akshaya AU - Achkar, Andrew PY - 2016/10/03 Y2 - 2024/03/29 TI - Lane Discovery in Traffic Video JF - Journal of Computational Vision and Imaging Systems JA - J. Comp. Vis. Imag. Sys. VL - 2 IS - 1 SE - Articles DO - 10.15353/vsnl.v2i1.125 UR - https://openjournals.uwaterloo.ca/index.php/vsl/article/view/125 SP - AB - <span>Video sensing has become very important in Intelligent Transportation Systems (ITS) due to its relative low cost and non-invasive deployment. An effective ITS requires detailed traffic information, including vehicle volume counts for each lane in surveillance video of a highway or an intersection. The multiple-target, vehicle-tracking and counting problem is most reliably solved in a reduced space defined by the constraints of the vehicles driving within lanes. This requires lanes to be pre-specified. An off-line pre-processing method is presented which automatically discovers traffic lanes from vehicle motion in uncalibrated video from a stationary camera. A moving vehicle density map is constructed, then multiple lane curves are fitted. Traffic lanes are found without relying on possibly noisy tracked vehicle trajectories.</span> ER -