Open AccessLane Discovery in Traffic Video
Author(s) -
Nicholas Miller,
David M. Swart,
Akshaya Mishra,
Andrew Achkar
Publication year - 1969
Publication title -
journal of computational vision and imaging systems
Language(s) - English
Resource type - Journals
ISSN - 2562-0444
DOI - 10.15353/vsnl.v2i1.125
Subject(s) - intersection (aeronautics) , computer science , computer vision , software deployment , artificial intelligence , vehicle tracking system , volume (thermodynamics) , intelligent transportation system , tracking (education) , line (geometry) , video processing , real time computing , transport engineering , engineering , mathematics , psychology , pedagogy , physics , geometry , segmentation , quantum mechanics , operating system
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.