Efficient Solution of Point-Line Absolute Pose

Petr Hruby, Timothy Duff, Marc Pollefeys; Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2024, pp. 21316-21325

Abstract


We revisit certain problems of pose estimation based on 3D--2D correspondences between features which may be points or lines. Specifically we address the two previously-studied minimal problems of estimating camera extrinsics from p \in \ 1 2 \ point--point correspondences and l=3-p line--line correspondences. To the best of our knowledge all of the previously-known practical solutions to these problems required computing the roots of degree \ge 4 (univariate) polynomials when p=2 or degree \ge 8 polynomials when p=1. We describe and implement two elementary solutions which reduce the degrees of the needed polynomials from 4 to 2 and from 8 to 4 respectively. We show experimentally that the resulting solvers are numerically stable and fast: when compared to the previous state-of-the art we may obtain nearly an order of magnitude speedup. The code is available at https://github.com/petrhruby97/efficient_absolute

Related Material


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[bibtex]
@InProceedings{Hruby_2024_CVPR, author = {Hruby, Petr and Duff, Timothy and Pollefeys, Marc}, title = {Efficient Solution of Point-Line Absolute Pose}, booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)}, month = {June}, year = {2024}, pages = {21316-21325} }