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Making Minimal Solvers for Absolute Pose Estimation Compact and Robust

Larsson, Viktor LU ; Kukelova, Zuzana and Zheng, Yinqiang (2017) 16th IEEE International Conference on Computer Vision, ICCV 2017 p.2335-2343
Abstract

In this paper we present new techniques for constructing compact and robust minimal solvers for absolute pose estimation. We focus on the P4Pfr problem, but the methods we propose are applicable to a more general setting. Previous approaches to P4Pfr suffer from artificial degeneracies which come from their formulation and not the geometry of the original problem. In this paper we show how to avoid these false degeneracies to create more robust solvers. Combined with recently published techniques for Gröbner basis solvers we are also able to construct solvers which are significantly smaller. We evaluate our solvers on both real and synthetic data, and show improved performance compared to competing solvers. Finally we show that our... (More)

In this paper we present new techniques for constructing compact and robust minimal solvers for absolute pose estimation. We focus on the P4Pfr problem, but the methods we propose are applicable to a more general setting. Previous approaches to P4Pfr suffer from artificial degeneracies which come from their formulation and not the geometry of the original problem. In this paper we show how to avoid these false degeneracies to create more robust solvers. Combined with recently published techniques for Gröbner basis solvers we are also able to construct solvers which are significantly smaller. We evaluate our solvers on both real and synthetic data, and show improved performance compared to competing solvers. Finally we show that our techniques can be directly applied to the P3.5Pf problem to get a non-degenerate solver, which is competitive with the current state-of-the-art.

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author
; and
organization
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
host publication
Proceedings - 2017 IEEE International Conference on Computer Vision, ICCV 2017
article number
8237516
pages
9 pages
publisher
IEEE - Institute of Electrical and Electronics Engineers Inc.
conference name
16th IEEE International Conference on Computer Vision, ICCV 2017
conference location
Venice, Italy
conference dates
2017-10-22 - 2017-10-29
external identifiers
  • scopus:85041924628
ISBN
9781538610329
DOI
10.1109/ICCV.2017.254
language
English
LU publication?
yes
id
2e8987b2-0aab-4d3c-b178-16f4cb17cc73
date added to LUP
2018-02-22 08:59:44
date last changed
2022-09-06 09:57:22
@inproceedings{2e8987b2-0aab-4d3c-b178-16f4cb17cc73,
  abstract     = {{<p>In this paper we present new techniques for constructing compact and robust minimal solvers for absolute pose estimation. We focus on the P4Pfr problem, but the methods we propose are applicable to a more general setting. Previous approaches to P4Pfr suffer from artificial degeneracies which come from their formulation and not the geometry of the original problem. In this paper we show how to avoid these false degeneracies to create more robust solvers. Combined with recently published techniques for Gröbner basis solvers we are also able to construct solvers which are significantly smaller. We evaluate our solvers on both real and synthetic data, and show improved performance compared to competing solvers. Finally we show that our techniques can be directly applied to the P3.5Pf problem to get a non-degenerate solver, which is competitive with the current state-of-the-art.</p>}},
  author       = {{Larsson, Viktor and Kukelova, Zuzana and Zheng, Yinqiang}},
  booktitle    = {{Proceedings - 2017 IEEE International Conference on Computer Vision, ICCV 2017}},
  isbn         = {{9781538610329}},
  language     = {{eng}},
  month        = {{12}},
  pages        = {{2335--2343}},
  publisher    = {{IEEE - Institute of Electrical and Electronics Engineers Inc.}},
  title        = {{Making Minimal Solvers for Absolute Pose Estimation Compact and Robust}},
  url          = {{http://dx.doi.org/10.1109/ICCV.2017.254}},
  doi          = {{10.1109/ICCV.2017.254}},
  year         = {{2017}},
}