Robust lane markings detection and road geometry computation |
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Authors: | A López J Serrat C Cañero F Lumbreras T Graf |
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Institution: | 1.Computer Vision Center and Comp. Science Department, Edifici O,Universitat Autònoma de Barcelona,Cerdanyola,Spain;2.Electronic Research,Volkswagen AG,Wolfsburg,Germany |
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Abstract: | Detection of lane markings based on a camera sensor can be a low-cost solution to lane departure and curve-over-speed warnings.
A number of methods and implementations have been reported in the literature. However, reliable detection is still an issue
because of cast shadows, worn and occluded markings, variable ambient lighting conditions, for example. We focus on increasing
detection reliability in two ways. First, we employed an image feature other than the commonly used edges: ridges, which we
claim addresses this problem better. Second, we adapted RANSAC, a generic robust estimation method, to fit a parametric model
of a pair of lane lines to the image features, based on both ridgeness and ridge orientation. In addition, the model was fitted
for the left and right lane lines simultaneously to enforce a consistent result. Four measures of interest for driver assistance
applications were directly computed from the fitted parametric model at each frame: lane width, lane curvature, and vehicle
yaw angle and lateral offset with regard the lane medial axis. We qualitatively assessed our method in video sequences captured
on several road types and under very different lighting conditions. We also quantitatively assessed it on synthetic but realistic
video sequences for which road geometry and vehicle trajectory ground truth are known. |
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