Making Minimal Solvers for Absolute Pose Estimation Compact and Robust

Viktor Larsson, Zuzana Kukelova, Yinqiang Zheng

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Sammanfattning

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.

Originalspråkengelska
Titel på värdpublikationProceedings - 2017 IEEE International Conference on Computer Vision, ICCV 2017
FörlagIEEE - Institute of Electrical and Electronics Engineers Inc.
Sidor2335-2343
Antal sidor9
ISBN (elektroniskt)9781538610329
DOI
StatusPublished - 2017 dec. 22
Evenemang16th IEEE International Conference on Computer Vision, ICCV 2017 - Venice, Italien
Varaktighet: 2017 okt. 222017 okt. 29

Konferens

Konferens16th IEEE International Conference on Computer Vision, ICCV 2017
Land/TerritoriumItalien
OrtVenice
Period2017/10/222017/10/29

Ämnesklassifikation (UKÄ)

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