DocumentCode :
253521
Title :
Minimal Solvers for Relative Pose with a Single Unknown Radial Distortion
Author :
Kuang, Yubin ; Solem, Jan Erik ; Kahl, Florian ; Astrom, Kalle
Author_Institution :
Centre for Math. Sci., Lund Univ., Lund, Sweden
fYear :
2014
fDate :
23-28 June 2014
Firstpage :
33
Lastpage :
40
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 Gröbner 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.
Keywords :
cameras; matrix algebra; numerical stability; polynomials; pose estimation; Grobner basis methods; essential matrix estimation; fast polynomial solvers; fundamental matrix estimation; numerical stability; partially calibrated camera pair; radial distortion; relative pose estimation; Calibration; Cameras; Estimation; Numerical stability; Polynomials; Transmission line matrix methods; minimal solver; radial distortion;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Vision and Pattern Recognition (CVPR), 2014 IEEE Conference on
Conference_Location :
Columbus, OH
Type :
conf
DOI :
10.1109/CVPR.2014.12
Filename :
6909406
Link To Document :
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