Match Selection and Refinement for Highly Accurate Two-View Structure from Motion
Abstract
We present an approach to enhance the accuracy of structure from motion (SfM) in the two-view case. We first answer the question: “fewer data with higher accuracy, or more data with less accuracy?” For this, we establish a relation between SfM errors and a function of the number of matches and their epipolar errors. Using an accuracy estimator of individual matches, we then propose a method to select a subset of matches that has a good quality vs. quantity compromise. We also propose a variant of least squares matching to refine match locations based on a focused grid and a multi-scale exploration. Experiments show that both selection and refinement contribute independently to a better accuracy. Their combination reduces errors by a factor of 1.1 to 2.0 for rotation, and 1.6 to 3.8 for translation.
Cite
Text
Liu et al. "Match Selection and Refinement for Highly Accurate Two-View Structure from Motion." European Conference on Computer Vision, 2014. doi:10.1007/978-3-319-10605-2_53Markdown
[Liu et al. "Match Selection and Refinement for Highly Accurate Two-View Structure from Motion." European Conference on Computer Vision, 2014.](https://mlanthology.org/eccv/2014/liu2014eccv-match/) doi:10.1007/978-3-319-10605-2_53BibTeX
@inproceedings{liu2014eccv-match,
title = {{Match Selection and Refinement for Highly Accurate Two-View Structure from Motion}},
author = {Liu, Zhe and Monasse, Pascal and Marlet, Renaud},
booktitle = {European Conference on Computer Vision},
year = {2014},
pages = {818-833},
doi = {10.1007/978-3-319-10605-2_53},
url = {https://mlanthology.org/eccv/2014/liu2014eccv-match/}
}