ML Anthology

Error Propagations for Local Bundle Adjustment

Alexandre Eudes, Maxime Lhuillier
CVPR 2009 pp. 2411-2418
doi:10.1109/CVPR.2009.5206824 /cvpr/2009/eudes2009cvpr-error/

Abstract

Local bundle adjustment (LBA) has recently been introduced to estimate the geometry of image sequences taken by a calibrated camera. Its advantage over standard (global) bundle adjustment is a great reduction of computational complexity, which allows real-time performances with a similar accuracy. However, no confidence measure on the LBA result such as uncertainty or covariance has yet been introduced. This paper introduces statistical models and estimation methods for uncertainty with two desirable properties: (1) uncertainty propagation along the sequence and (2) real-time calculation. We also explain why this problem is more complicated than it may appear at first glance, and we provide results on video sequences.

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Cite

Text

Eudes and Lhuillier. "Error Propagations for Local Bundle Adjustment." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2009. doi:10.1109/CVPR.2009.5206824

Markdown

[Eudes and Lhuillier. "Error Propagations for Local Bundle Adjustment." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2009.](https://mlanthology.org/cvpr/2009/eudes2009cvpr-error/) doi:10.1109/CVPR.2009.5206824

BibTeX

@inproceedings{eudes2009cvpr-error,
  title     = {{Error Propagations for Local Bundle Adjustment}},
  author    = {Eudes, Alexandre and Lhuillier, Maxime},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  year      = {2009},
  pages     = {2411-2418},
  doi       = {10.1109/CVPR.2009.5206824},
  url       = {https://mlanthology.org/cvpr/2009/eudes2009cvpr-error/}
}