ML Anthology

Using Galois Theory to Prove Structure from Motion Algorithms Are Optimal

David Nistér, Richard I. Hartley, Henrik Stewénius
CVPR 2007
doi:10.1109/CVPR.2007.383089 /cvpr/2007/nister2007cvpr-using/
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Cite

Text

Nistér et al. "Using Galois Theory to Prove Structure from Motion Algorithms Are Optimal." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2007. doi:10.1109/CVPR.2007.383089

Markdown

[Nistér et al. "Using Galois Theory to Prove Structure from Motion Algorithms Are Optimal." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2007.](https://mlanthology.org/cvpr/2007/nister2007cvpr-using/) doi:10.1109/CVPR.2007.383089

BibTeX

@inproceedings{nister2007cvpr-using,
  title     = {{Using Galois Theory to Prove Structure from Motion Algorithms Are Optimal}},
  author    = {Nistér, David and Hartley, Richard I. and Stewénius, Henrik},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  year      = {2007},
  doi       = {10.1109/CVPR.2007.383089},
  url       = {https://mlanthology.org/cvpr/2007/nister2007cvpr-using/}
}