UPnP: An Optimal O(n) Solution to the Absolute Pose Problem with Universal Applicability
Abstract
A large number of absolute pose algorithms have been presented in the literature. Common performance criteria are computational complexity, geometric optimality, global optimality, structural degeneracies, and the number of solutions. The ability to handle minimal sets of correspondences, resulting solution multiplicity, and generalized cameras are further desirable properties. This paper presents the first PnP solution that unifies all the above desirable properties within a single algorithm. We compare our result to state-of-the-art minimal, non-minimal, central, and non-central PnP algorithms, and demonstrate universal applicability, competitive noise resilience, and superior computational efficiency. Our algorithm is called Unified PnP (UPnP).
Cite
Text
Kneip et al. "UPnP: An Optimal O(n) Solution to the Absolute Pose Problem with Universal Applicability." European Conference on Computer Vision, 2014. doi:10.1007/978-3-319-10590-1_9Markdown
[Kneip et al. "UPnP: An Optimal O(n) Solution to the Absolute Pose Problem with Universal Applicability." European Conference on Computer Vision, 2014.](https://mlanthology.org/eccv/2014/kneip2014eccv-upnp/) doi:10.1007/978-3-319-10590-1_9BibTeX
@inproceedings{kneip2014eccv-upnp,
title = {{UPnP: An Optimal O(n) Solution to the Absolute Pose Problem with Universal Applicability}},
author = {Kneip, Laurent and Li, Hongdong and Seo, Yongduek},
booktitle = {European Conference on Computer Vision},
year = {2014},
pages = {127-142},
doi = {10.1007/978-3-319-10590-1_9},
url = {https://mlanthology.org/eccv/2014/kneip2014eccv-upnp/}
}