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