Leveraging Vision Reconstruction Pipelines for Satellite Imagery

ICCVW 2019 pp. 2139-2148

doi:10.1109/ICCVW.2019.00269 /iccvw/2019/zhang2019iccvw-leveraging/

Abstract

Reconstructing 3D geometry from satellite imagery is an important and growing topic of research. However, disparities exist between how this 3D reconstruction problem is handled in the remote sensing context and how multi-view reconstruction pipelines have been developed in the computer vision community. In this paper, we explore whether state-of-the-art reconstruction pipelines from the vision community can be applied to the satellite imagery. Along the way, we address several challenges adapting vision-based structure from motion and multi-view stereo methods. We show that vision pipelines can offer competitive speed and accuracy in the satellite context.

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Cite

Text

Zhang et al. "Leveraging Vision Reconstruction Pipelines for Satellite Imagery." IEEE/CVF International Conference on Computer Vision Workshops, 2019. doi:10.1109/ICCVW.2019.00269

Markdown

[Zhang et al. "Leveraging Vision Reconstruction Pipelines for Satellite Imagery." IEEE/CVF International Conference on Computer Vision Workshops, 2019.](https://mlanthology.org/iccvw/2019/zhang2019iccvw-leveraging/) doi:10.1109/ICCVW.2019.00269

BibTeX

@inproceedings{zhang2019iccvw-leveraging,
  title     = {{Leveraging Vision Reconstruction Pipelines for Satellite Imagery}},
  author    = {Zhang, Kai and Snavely, Noah and Sun, Jin},
  booktitle = {IEEE/CVF International Conference on Computer Vision Workshops},
  year      = {2019},
  pages     = {2139-2148},
  doi       = {10.1109/ICCVW.2019.00269},
  url       = {https://mlanthology.org/iccvw/2019/zhang2019iccvw-leveraging/}
}