ML Anthology

RoadTracer: Automatic Extraction of Road Networks from Aerial Images

Favyen Bastani, Songtao He, Sofiane Abbar, Mohammad Alizadeh, Hari Balakrishnan, Sanjay Chawla, Sam Madden, David DeWitt
CVPR 2018
doi:10.1109/CVPR.2018.00496 /cvpr/2018/bastani2018cvpr-roadtracer/

Abstract

Mapping road networks is currently both expensive and labor-intensive. High-resolution aerial imagery provides a promising avenue to automatically infer a road network. Prior work uses convolutional neural networks (CNNs) to detect which pixels belong to a road (segmentation), and then uses complex post-processing heuristics to infer graph connectivity. We show that these segmentation methods have high error rates because noisy CNN outputs are difficult to correct. We propose RoadTracer, a new method to automatically construct accurate road network maps from aerial images. RoadTracer uses an iterative search process guided by a CNN-based decision function to derive the road network graph directly from the output of the CNN. We compare our approach with a segmentation method on fifteen cities, and find that at a 5% error rate, RoadTracer correctly captures 45% more junctions across these cities.

PDF CVPR Semantic Scholar

Cite

Text

Bastani et al. "RoadTracer: Automatic Extraction of Road Networks from Aerial Images." Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2018. doi:10.1109/CVPR.2018.00496

Markdown

[Bastani et al. "RoadTracer: Automatic Extraction of Road Networks from Aerial Images." Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2018.](https://mlanthology.org/cvpr/2018/bastani2018cvpr-roadtracer/) doi:10.1109/CVPR.2018.00496

BibTeX

@inproceedings{bastani2018cvpr-roadtracer,
  title     = {{RoadTracer: Automatic Extraction of Road Networks from Aerial Images}},
  author    = {Bastani, Favyen and He, Songtao and Abbar, Sofiane and Alizadeh, Mohammad and Balakrishnan, Hari and Chawla, Sanjay and Madden, Sam and DeWitt, David},
  booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  year      = {2018},
  doi       = {10.1109/CVPR.2018.00496},
  url       = {https://mlanthology.org/cvpr/2018/bastani2018cvpr-roadtracer/}
}