Minimal Solvers for Relative Pose with a Single Unknown Radial Distortion
Kuang, Yubin; Solem, Jan Erik; Kahl, Fredrik; Åström, Karl (2014). Minimal Solvers for Relative Pose with a Single Unknown Radial Distortion Computer Vision and Pattern Recognition (CVPR), 2014 IEEE Conference on, 33 - 40. IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2014), 2014. Columbus, Ohio, United States: IEEE - Institute of Electrical and Electronics Engineers Inc.
Conference Proceeding/Paper
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Published
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English
Authors:
Kuang, Yubin
;
Solem, Jan Erik
;
Kahl, Fredrik
;
Åström, Karl
Department:
Mathematics (Faculty of Engineering)
Mathematical Imaging Group
ELLIIT: the Linköping-Lund initiative on IT and mobile communication
Research Group:
Mathematical Imaging Group
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.
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