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A Holistic Framework for Addressing the World using Machine Learning

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Author(s)
Demir, Ilke
•
Hughes, Forest
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Raj, Aman
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Dhruv, Kaunil
•
Muddala, Suryanarayana Murthy
•
Garg, Sanyam
•
Doo, Barrett
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Raskar, Ramesh
Date Issued
June 2018
Publisher
IEEE
Citation
Demir, Ilke, Hughes, Forest, Raj, Aman, Dhruv, Kaunil, Muddala, Suryanarayana Murthy et al. 2018. "A Holistic Framework for Addressing the World using Machine Learning."
Version
Author's final manuscript
Abstract
© 2018 IEEE. Millions of people are disconnected from basic services due to lack of adequate addressing. We propose an automatic generative algorithm to create street addresses from satellite imagery. Our addressing scheme is coherent with the street topology, linear and hierarchical to follow human perception, and universal to be used as a unified geocoding system. Our algorithm starts with extracting road segments using deep learning and partitions the road network into regions. Then regions, streets, and address cells are named using proximity computations. We also extend our addressing scheme to cover inaccessible areas, to be flexible for changes, and to lead as a pioneer for a unified geodatabase.
MIT Department
Massachusetts Institute of Technology. Media Laboratory
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Creative Commons Attribution-Noncommercial-Share Alike
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DOI of Published Version
10.1109/cvprw.2018.00245
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