The authors introduce a lane marker detection algorithm that integrates 3D attributes as well as 3D relations between local edges and semi-global contours in a Bayesian framework. The algorithm is parameter free and does not make use of any heuristic assumptions. The reasoning is based on the complete conditional probabilities of the different cues which are estimated from a training set. The importance of the individual visual cues can be computed using a standard measure and the cues can then be combined in an optimal way. In addition the authors show that when doing 3D reasoning, the uncertainties connected to the reconstruction process need to be taken into account to make the reasoning process more stable. The results are shown on a publicly available data set.
Bayesian reasoning using 3D relations for lane marker detection
Ein Bayes-Verfahren mit 3D-Beziehungen für die Fahrspurerkennung
2009
8 Seiten, 7 Bilder, 2 Tabellen, 12 Quellen
Aufsatz (Konferenz)
Englisch
Lidar-based lane marker detection and mapping
IEEE | 2008
|Lidar-Based Lane Marker Detection and Mapping
British Library Conference Proceedings | 2008
|