Robocodes: Towards Generative Street Addresses from Satellite Imagery

Abstract

We describe our automatic generative algorithm to create street addresses (Robocodes) from satellite images by learning and labeling regions, roads, and blocks. 75% of the world lacks street addresses [12]. According to the United Nations, this means 4 billion people are 'invisible'. Recent initiatives tend to name unknown areas by geocoding, which uses latitude and longitude information. Nevertheless settlements abut roads and such addressing schemes are not coherent with the road topology. Instead, our algorithm starts with extracting roads and junctions from satellite imagery utilizing deep learning. Then, it uniquely labels the regions, roads, and houses using some graph- and proximity-based algorithms. We present our results on both cities in mapped areas and in developing countries. We also compare productivity based on current ad-hoc and new complete addresses. We conclude with contrasting our generative addresses to current industrial and open solutions.

Cite

Text

Demir et al. "Robocodes: Towards Generative Street Addresses from Satellite Imagery." IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2017. doi:10.1109/CVPRW.2017.192

Markdown

[Demir et al. "Robocodes: Towards Generative Street Addresses from Satellite Imagery." IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2017.](https://mlanthology.org/cvprw/2017/demir2017cvprw-robocodes/) doi:10.1109/CVPRW.2017.192

BibTeX

@inproceedings{demir2017cvprw-robocodes,
  title     = {{Robocodes: Towards Generative Street Addresses from Satellite Imagery}},
  author    = {Demir, Ilke and Hughes, Forest and Raj, Aman and Tsourides, Kleovoulos and Ravichandran, Divyaa and Muddala, Suryanarayana Murthy and Dhruv, Kaunil and Garg, Sanyam and Malhotra, Jatin and Doo, Barrett and Kermani, Grace and Raskar, Ramesh},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops},
  year      = {2017},
  pages     = {1486-1495},
  doi       = {10.1109/CVPRW.2017.192},
  url       = {https://mlanthology.org/cvprw/2017/demir2017cvprw-robocodes/}
}