Ortho-Image Analysis for Producing Lane-Level Highway Maps
Abstract
This paper presents new aerial image analysis algorithms that, from highway ortho-images, produce lane-level detailed maps. We analyze screenshots of road vectors to obtain the relevant spatial and photometric cues of road image-regions. We then refine the obtained patterns to generate hypotheses about the true road-lanes. A road-lane hypothesis, since it explains only a part of the true road-lane, is then linked to other hypotheses to completely delineate boundaries of the true road-lanes. Finally, some of the refined image cues about the underlying road network are used to guide a linking process of road-lane hypotheses. We tested the accuracy and robustness of our algorithms with high-resolution, inter-city highway ortho-images. Experimental results show promise in producing lane-level detailed highway maps from ortho-image analysis - 89% of the true road-lane boundary pixels were successfully detected and 337 out of 417 true road-lanes were correctly recovered.
BibTeX
@conference{Seo-2012-7636,author = {Young-Woo Seo and Christopher Urmson and David Wettergreen},
title = {Ortho-Image Analysis for Producing Lane-Level Highway Maps},
booktitle = {Proceedings of 20th International Conference on Advances in Geographic Information Systems (SIGSPATIAL '12)},
year = {2012},
month = {November},
pages = {506 - 509},
publisher = {ACM},
keywords = {lane-level highway map extraction, ortho image anaysis, computer vision, machine learning},
}