Minimal Solvers for Relative Pose with a Single Unknown Radial Distortion

Yubin Kuang; Jan Erik Solem; Fredrik Kahl; Karl Åström

doi:10.1109/CVPR.2014.12

Minimal Solvers for Relative Pose with a Single Unknown Radial Distortion

Yubin Kuang, Jan Erik Solem, Fredrik Kahl, Karl Åström

Forskningsoutput: Kapitel i bok/rapport/Conference proceeding › Konferenspaper i proceeding › Peer review

Sammanfattning

In this paper, we study the problems of estimating relative
pose between two cameras in the presence of radial distortion.
Specifically, we consider minimal problems where
one of the cameras has no or known radial distortion. There
are three useful cases for this setup with a single unknown
distortion: (i) fundamental matrix estimation where the two
cameras are uncalibrated, (ii) essential matrix estimation
for a partially calibrated camera pair, (iii) essential matrix
estimation for one calibrated camera and one camera
with unknown focal length. We study the parameterization
of these three problems and derive fast polynomial solvers
based on Gr¨obner basis methods. We demonstrate the numerical
stability of the solvers on synthetic data. The minimal
solvers have also been applied to real imagery with
convincing results.

Originalspråk	engelska
Titel på värdpublikation	Computer Vision and Pattern Recognition (CVPR), 2014 IEEE Conference on
Förlag	IEEE - Institute of Electrical and Electronics Engineers Inc.
Sidor	33-40
Antal sidor	8
DOI	https://doi.org/10.1109/CVPR.2014.12
Status	Published - 2014
Evenemang	IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2014), 2014 - Columbus, Ohio, USA Varaktighet: 2014 juni 24 → 2014 juni 27

Publikationsserier

Namn
ISSN (tryckt)	1063-6919

Konferens

Konferens	IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2014), 2014
Land/Territorium	USA
Ort	Columbus, Ohio
Period	2014/06/24 → 2014/06/27

Ämnesklassifikation (UKÄ)

Matematik

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10.1109/CVPR.2014.12

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@inproceedings{d2cf23e9e9b54ebc82b750929cca3c75,

title = "Minimal Solvers for Relative Pose with a Single Unknown Radial Distortion",

abstract = "In this paper, we study the problems of estimating relative pose between two cameras in the presence of radial distortion. Specifically, we consider minimal problems where one of the cameras has no or known radial distortion. There are three useful cases for this setup with a single unknown distortion: (i) fundamental matrix estimation where the two cameras are uncalibrated, (ii) essential matrix estimation for a partially calibrated camera pair, (iii) essential matrix estimation for one calibrated camera and one camera with unknown focal length. We study the parameterization of these three problems and derive fast polynomial solvers based on Gr¨obner basis methods. We demonstrate the numerical stability of the solvers on synthetic data. The minimal solvers have also been applied to real imagery with convincing results.",

author = "Yubin Kuang and Solem, {Jan Erik} and Fredrik Kahl and Karl {\AA}str{\"o}m",

year = "2014",

doi = "10.1109/CVPR.2014.12",

language = "English",

publisher = "IEEE - Institute of Electrical and Electronics Engineers Inc.",

pages = "33--40",

booktitle = "Computer Vision and Pattern Recognition (CVPR), 2014 IEEE Conference on",

address = "United States",

note = "IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2014), 2014 ; Conference date: 24-06-2014 Through 27-06-2014",

}

Kuang, Y, Solem, JE, Kahl, F & Åström, K 2014, Minimal Solvers for Relative Pose with a Single Unknown Radial Distortion. i Computer Vision and Pattern Recognition (CVPR), 2014 IEEE Conference on. IEEE - Institute of Electrical and Electronics Engineers Inc., s. 33-40, IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2014), 2014, Columbus, Ohio, USA, 2014/06/24. https://doi.org/10.1109/CVPR.2014.12

Minimal Solvers for Relative Pose with a Single Unknown Radial Distortion. / Kuang, Yubin; Solem, Jan Erik; Kahl, Fredrik et al.
Computer Vision and Pattern Recognition (CVPR), 2014 IEEE Conference on. IEEE - Institute of Electrical and Electronics Engineers Inc., 2014. s. 33-40.

Forskningsoutput: Kapitel i bok/rapport/Conference proceeding › Konferenspaper i proceeding › Peer review

TY - GEN

T1 - Minimal Solvers for Relative Pose with a Single Unknown Radial Distortion

AU - Kuang, Yubin

AU - Solem, Jan Erik

AU - Kahl, Fredrik

AU - Åström, Karl

PY - 2014

Y1 - 2014

N2 - In this paper, we study the problems of estimating relative pose between two cameras in the presence of radial distortion. Specifically, we consider minimal problems where one of the cameras has no or known radial distortion. There are three useful cases for this setup with a single unknown distortion: (i) fundamental matrix estimation where the two cameras are uncalibrated, (ii) essential matrix estimation for a partially calibrated camera pair, (iii) essential matrix estimation for one calibrated camera and one camera with unknown focal length. We study the parameterization of these three problems and derive fast polynomial solvers based on Gr¨obner basis methods. We demonstrate the numerical stability of the solvers on synthetic data. The minimal solvers have also been applied to real imagery with convincing results.

AB - In this paper, we study the problems of estimating relative pose between two cameras in the presence of radial distortion. Specifically, we consider minimal problems where one of the cameras has no or known radial distortion. There are three useful cases for this setup with a single unknown distortion: (i) fundamental matrix estimation where the two cameras are uncalibrated, (ii) essential matrix estimation for a partially calibrated camera pair, (iii) essential matrix estimation for one calibrated camera and one camera with unknown focal length. We study the parameterization of these three problems and derive fast polynomial solvers based on Gr¨obner basis methods. We demonstrate the numerical stability of the solvers on synthetic data. The minimal solvers have also been applied to real imagery with convincing results.

U2 - 10.1109/CVPR.2014.12

DO - 10.1109/CVPR.2014.12

M3 - Paper in conference proceeding

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BT - Computer Vision and Pattern Recognition (CVPR), 2014 IEEE Conference on

PB - IEEE - Institute of Electrical and Electronics Engineers Inc.

T2 - IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2014), 2014

Y2 - 24 June 2014 through 27 June 2014

ER -

Minimal Solvers for Relative Pose with a Single Unknown Radial Distortion

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