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Towards HD Maps from Aerial Imagery: Robust Lane Marking Segmentation Using Country-Scale Imagery

By Peter Fischer, Seyed Majid Azimi, Robert Roschlaub and Thomas Krauß


The upraise of autonomous driving technologies asks for maps characterized bya broad range of features and quality parameters, in contrast to traditional navigation maps which in most cases are enriched graph-based models. This paper tackles several uncertainties within the domain of HD Maps. The authors give an overview about the current state in extracting road features from aerial imagery for creating HD maps, before shifting the focus of the paper towards remote sensing technology. Possible data sources and their relevant parameters are listed. A random forest classifier is used, showing how these data can deliver HD Maps on a country-scale, meeting specific quality parameters

Topics: autonomous driving, HD maps, aerial imagery, Geography (General), G1-922
Publisher: MDPI AG
Year: 2018
DOI identifier: 10.3390/ijgi7120458
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