Fast and Accurate Camera Covariance Computation for Large 3D Reconstruction
Abstract
Estimating uncertainty of camera parameters computed in Structure from Motion (SfM) is an important tool for evaluating the quality of the reconstruction and guiding the reconstruction process. Yet, the quality of the estimated parameters of large reconstructions has been rarely evaluated due to the computational challenges. We present a new algorithm which employs the sparsity of the uncertainty propagation and speeds the computation up about ten times wrt previous approaches. Our computation is accurate and does not use any approximations. We can compute uncertainties of thousands of cameras in tens of seconds on a standard PC. We also demonstrate that our approach can be effectively used for reconstructions of any size by applying it to smaller sub-reconstructions.
Cite
Text
Polic et al. "Fast and Accurate Camera Covariance Computation for Large 3D Reconstruction." Proceedings of the European Conference on Computer Vision (ECCV), 2018. doi:10.1007/978-3-030-01216-8_42Markdown
[Polic et al. "Fast and Accurate Camera Covariance Computation for Large 3D Reconstruction." Proceedings of the European Conference on Computer Vision (ECCV), 2018.](https://mlanthology.org/eccv/2018/polic2018eccv-fast/) doi:10.1007/978-3-030-01216-8_42BibTeX
@inproceedings{polic2018eccv-fast,
title = {{Fast and Accurate Camera Covariance Computation for Large 3D Reconstruction}},
author = {Polic, Michal and Forstner, Wolfgang and Pajdla, Tomas},
booktitle = {Proceedings of the European Conference on Computer Vision (ECCV)},
year = {2018},
doi = {10.1007/978-3-030-01216-8_42},
url = {https://mlanthology.org/eccv/2018/polic2018eccv-fast/}
}