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.
Originalspråk | engelska |
---|---|
Titel på värdpublikation | Proceedings - 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2021 |
Förlag | IEEE Computer Society |
Sidor | 3663-3672 |
Antal sidor | 10 |
ISBN (elektroniskt) | 9781665448994 |
DOI | |
Status | Published - 2021 |
Evenemang | 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2021 - Virtual, Online, USA Varaktighet: 2021 juni 19 → 2021 juni 25 |
Publikationsserier
Namn | IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops |
---|---|
ISSN (tryckt) | 2160-7508 |
ISSN (elektroniskt) | 2160-7516 |
Konferens
Konferens | 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2021 |
---|---|
Land/Territorium | USA |
Ort | Virtual, Online |
Period | 2021/06/19 → 2021/06/25 |
Bibliografisk information
Publisher Copyright:© 2021 IEEE.
Ämnesklassifikation (UKÄ)
- Beräkningsmatematik