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1997 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'97)
Lens distortion calibration using point correspondences
Puerto Rico
June 17-June 19
ISBN: 0-8186-7822-4
| ASCII Text | x | ||
| G.P. Stein, "Lens distortion calibration using point correspondences," 2012 IEEE Conference on Computer Vision and Pattern Recognition, pp. 602, 1997 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'97), 1997. | |||
| BibTex | x | ||
| @article{ 10.1109/CVPR.1997.609387, author = {G.P. Stein}, title = {Lens distortion calibration using point correspondences}, journal ={2012 IEEE Conference on Computer Vision and Pattern Recognition}, volume = {0}, year = {1997}, issn = {1063-6919}, pages = {602}, doi = {http://doi.ieeecomputersociety.org/10.1109/CVPR.1997.609387}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, } | |||
| RefWorks Procite/RefMan/Endnote | x | ||
| TY - CONF JO - 2012 IEEE Conference on Computer Vision and Pattern Recognition TI - Lens distortion calibration using point correspondences SN - 1063-6919 SP EP A1 - G.P. Stein, PY - 1997 KW - feature extraction; lens distortion calibration; point correspondences; multiple views; pinhole cameras; constraints; feature detection; calibration; 3D reconstruction; accuracy VL - 0 JA - 2012 IEEE Conference on Computer Vision and Pattern Recognition ER - | |||
This paper describes a new method for lens distortion calibration using only point correspondences in multiple views, without the need to know either the 3D location of the points or the camera locations. The standard lens distortion model is a model of the deviations of a real camera from the ideal pinhole or projective camera model. Given multiple views of a set of corresponding points taken by ideal pinhole cameras there exist epipolar and trilinear constraints among pairs and triplets of these views. In practice, due to noise in the feature detection and due to lens distortion these constraints do not hold exactly and we get some error. The calibration is a search for the lens distortion parameters that minimize this error. Using simulation and experimental results with real images we explore the properties of this method. We describe the use of this method with the standard lens distortion model, radial and decentering, but it could also be used with any other parametric distortion models. Finally we demonstrate that lens distortion calibration improves the accuracy of 3D reconstruction.
Index Terms:
feature extraction; lens distortion calibration; point correspondences; multiple views; pinhole cameras; constraints; feature detection; calibration; 3D reconstruction; accuracy
Citation:
G.P. Stein, "Lens distortion calibration using point correspondences," cvpr, pp.602, 1997 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'97), 1997
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