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Statements

Subject Item
n2:RIV%2F68407700%3A21230%2F07%3A03135485%21RIV09-MSM-21230___
rdf:type
n9:Vysledek skos:Concept
dcterms:description
Epipolar geometry and relative camera pose computation are examples of tasks which can be formulated as minimal problems and solved from a minimal number of image points. Finding the solution leads to solving systems of algebraic equations. Often, these systems are not trivial and therefore special algorithms have to be designed to achieve numerical robustness and computational efficiency. In this paper we provide a solution to the problem of estimating radial distortion and epipolar geometry from eight correspondences in two images. Unlike previous algorithms, which were able to solve the problem from nine correspondences only, we enforce the determinant of the fundamental matrix be zero. This leads to a system of eight quadratic and one cubic equation in nine variables. We simplify this system by eliminating six of these variables. Then, we solve the system by finding eigenvectors of an action matrix of a suitably chosen polynomial. We show how to construct the action matrix without Epipolar geometry and relative camera pose computation are examples of tasks which can be formulated as minimal problems and solved from a minimal number of image points. Finding the solution leads to solving systems of algebraic equations. Often, these systems are not trivial and therefore special algorithms have to be designed to achieve numerical robustness and computational efficiency. In this paper we provide a solution to the problem of estimating radial distortion and epipolar geometry from eight correspondences in two images. Unlike previous algorithms, which were able to solve the problem from nine correspondences only, we enforce the determinant of the fundamental matrix be zero. This leads to a system of eight quadratic and one cubic equation in nine variables. We simplify this system by eliminating six of these variables. Then, we solve the system by finding eigenvectors of an action matrix of a suitably chosen polynomial. We show how to construct the action matrix without Epipolar geometry and relative camera pose computation are examples of tasks which can be formulated as minimal problems and solved from a minimal number of image points. Finding the solution leads to solving systems of algebraic equations. Often, these systems are not trivial and therefore special algorithms have to be designed to achieve numerical robustness and computational efficiency. In this paper we provide a solution to the problem of estimating radial distortion and epipolar geometry from eight correspondences in two images. Unlike previous algorithms, which were able to solve the problem from nine correspondences only, we enforce the determinant of the fundamental matrix be zero. This leads to a system of eight quadratic and one cubic equation in nine variables. We simplify this system by eliminating six of these variables. Then, we solve the system by finding eigenvectors of an action matrix of a suitably chosen polynomial. We show how to construct the action matrix without
dcterms:title
A minimal solution to the autocalibration of radial distortion A minimal solution to the autocalibration of radial distortion A minimal solution to the autocalibration of radial distortion
skos:prefLabel
A minimal solution to the autocalibration of radial distortion A minimal solution to the autocalibration of radial distortion A minimal solution to the autocalibration of radial distortion
skos:notation
RIV/68407700:21230/07:03135485!RIV09-MSM-21230___
n3:aktivita
n7:Z
n3:aktivity
Z(MSM6840770038)
n3:dodaniDat
n8:2009
n3:domaciTvurceVysledku
n18:6245269 n18:6349390
n3:druhVysledku
n19:D
n3:duvernostUdaju
n12:S
n3:entitaPredkladatele
n6:predkladatel
n3:idSjednocenehoVysledku
407948
n3:idVysledku
RIV/68407700:21230/07:03135485
n3:jazykVysledku
n20:eng
n3:klicovaSlova
Gröbner basis; minimal problems; radial distortion
n3:klicoveSlovo
n14:minimal%20problems n14:radial%20distortion n14:Gr%C3%B6bner%20basis
n3:kontrolniKodProRIV
[59085CC1B0ED]
n3:mistoKonaniAkce
Minneapolis
n3:mistoVydani
Los Alamitos
n3:nazevZdroje
CVPR 2007: Proceedings of the Computer Vision and Pattern Recognition conference
n3:obor
n15:JD
n3:pocetDomacichTvurcuVysledku
2
n3:pocetTvurcuVysledku
2
n3:rokUplatneniVysledku
n8:2007
n3:tvurceVysledku
Pajdla, Tomáš Kúkelová, Zuzana
n3:typAkce
n4:WRD
n3:zahajeniAkce
2007-06-18+02:00
n3:zamer
n13:MSM6840770038
s:issn
1053-587X
s:numberOfPages
7
n21:hasPublisher
IEEE Computer Society
n16:isbn
1-4244-1180-7
n17:organizacniJednotka
21230