Towards Large-Scale City Reconstruction from Satellites

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9909)

Abstract

Automatic city modeling from satellite imagery is one of the biggest challenges in urban reconstruction. Existing methods produce at best rough and dense Digital Surface Models. Inspired by recent works on semantic 3D reconstruction and region-based stereovision, we propose a method for producing compact, semantic-aware and geometrically accurate 3D city models from stereo pair of satellite images. Our approach relies on two key ingredients. First, geometry and semantics are retrieved simultaneously bringing robustness to occlusions and to low image quality. Second, we operate at the scale of geometric atomic region which allows the shape of urban objects to be well preserved, and a gain in scalability and efficiency. We demonstrate the potential of our algorithm by reconstructing different cities around the world in a few minutes.

Keywords

3D reconstruction City modeling Satellite imagery Urban scenes 

Notes

Acknowledgments

This work was supported by Luxcarta. The authors thank Qian-Yi Zhou, Lionel Laurore, Justin Hyland, Véronique Poujade and Frédéric Trastour for datasets and technical discussions.

Supplementary material

419978_1_En_6_MOESM1_ESM.pdf (14 mb)
Supplementary material 1 (pdf 14289 KB)

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Copyright information

© Springer International Publishing AG 2016

Authors and Affiliations

  1. 1.InriaSophia AntipolisFrance

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