Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/36071
Title: Estimation of the lens distortion model by minimizing a line reprojection error
Authors: Santana-Cedrés, Daniel 
Gomez, Luis 
Alemán-Flores, Miguel 
Salgado de la Nuez, Agustín Javier 
Esclarín, Julio 
Mazorra, Luis 
Alvarez, Luis 
UNESCO Clasification: 220990 Tratamiento digital. Imágenes
120602 Ecuaciones diferenciales
120601 Construcción de algoritmos
120326 Simulación
Keywords: Camera sensor
Lens distortion
Homography estimation
Reprojection error
Issue Date: 2017
Journal: IEEE Sensors Journal 
Abstract: Most techniques for camera calibration that use planar calibration patterns require the computation of a lens distortion model and a homography. Both are simultaneously refined using a bundle adjustment that minimizes the reprojection error of a collection of points when projected from the scene onto the camera sensor. These points are usually the corners of the rectangles of a calibration pattern. However, if the lens shows a significant distortion, the location and matching of the corners can be difficult and inaccurate. To cope with this problem, instead of point correspondences, we propose to use line correspondences to compute the reprojection error. We have designed a fully automatic algorithm to estimate the lens distortion model and the homography by computing line correspondences and minimizing the line reprojection error. In the experimental setup, we focus on the analysis of the quality of the obtained lens distortion model. We present some experiments that show that the proposed method outperforms the results obtained by standard methods to compute lens distortion models based on line rectification.
URI: http://hdl.handle.net/10553/36071
ISSN: 1530-437X
DOI: 10.1109/JSEN.2017.2677475
Source: IEEE Sensors Journal[ISSN 1530-437X],v. 17 (2677475), p. 2848-2855
Appears in Collections:Artículos
Show full item record

SCOPUSTM   
Citations

8
checked on Feb 28, 2021

Page view(s)

55
checked on Feb 27, 2021

Google ScholarTM

Check

Altmetric


Share



Export metadata



Items in accedaCRIS are protected by copyright, with all rights reserved, unless otherwise indicated.