We present a robust and real time approach to lane marker detection in urban streets. It is based on generating a top view of the road, filtering using selective oriented Gaussian filters, using RANSAC line fitting to give initial guesses to a new and fast RANSAC algorithm for fitting Bezier Splines, which is then followed by a post-processing step. Our algorithm can detect all lanes in still images of the street in various conditions, while operating at a rate of 50 Hz and achieving comparable results to previous techniques.
Real time detection of lane markers in urban streets
01.06.2008
1409879 byte
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
Real time Detection of Lane Markers in Urban Streets
British Library Conference Proceedings | 2008
|Real Time Detection and Classification of Arrow Markings in Urban Streets
Online Contents | 2018
|Real Time Detection and Classification of Arrow Markings in Urban Streets
Springer Verlag | 2018
|A Driver Behavior-Based Lane-Changing Model for Urban Arterial Streets
British Library Online Contents | 2014
|