Fast solvers for minimal radial distortion relative pose problems

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Sammanfattning

In this paper we present a unified formulation for a large class of relative pose problems with radial distortion and varying calibration. For minimal cases, we show that one can eliminate the number of parameters down to one to three. The relative pose can then be expressed using varying calibration constraints on the fundamental matrix, with entries that are polynomial in the parameters. We can then apply standard techniques based on the action matrix and Sturm sequences to construct our solvers. This enables efficient solvers for a large class of relative pose problems with radial distortion, using a common framework. We evaluate a number of these solvers for robust two-view inlier and epipolar geometry estimation, used as minimal solvers in RANSAC.

Originalspråkengelska
Titel på värdpublikationProceedings - 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2021
FörlagIEEE Computer Society
Sidor3663-3672
Antal sidor10
ISBN (elektroniskt)9781665448994
DOI
StatusPublished - 2021
Evenemang2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2021 - Virtual, Online, USA
Varaktighet: 2021 juni 192021 juni 25

Publikationsserier

NamnIEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops
ISSN (tryckt)2160-7508
ISSN (elektroniskt)2160-7516

Konferens

Konferens2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2021
Land/TerritoriumUSA
OrtVirtual, Online
Period2021/06/192021/06/25

Bibliografisk information

Publisher Copyright:
© 2021 IEEE.

Ämnesklassifikation (UKÄ)

  • Beräkningsmatematik

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