Uncertainty evaluation of camera model parameters

Camera calibration is an important task for vision-based measurement systems since it estimates the values of camera model parameters. The uncertainty of these parameters is required in order to evaluate the uncertainty of vision-based final measurements. This paper deals with a procedure for the propagation of the uncertainty through calibration algorithms and mainly focuses on the algorithms for the localization of target points in calibration images. Numerical results will be reported highlighting the usefulness of the method in the set-up of a vision-based measurement system.

[1]  Andrew W. Fitzgibbon,et al.  Direct Least Square Fitting of Ellipses , 1999, IEEE Trans. Pattern Anal. Mach. Intell..

[2]  Alistair B. Forbes,et al.  Software Support for Metrology Best Practice Guide No. 4 , 2007 .

[3]  Won S. Kim,et al.  Performance Analysis and Validation of a Stereo Vision System , 2005, 2005 IEEE International Conference on Systems, Man and Cybernetics.

[4]  Andrea Fusiello,et al.  Rigorous Computing in Computer Vision , 2005, VVG.

[5]  Alfredo Paolillo,et al.  Covariance Propagation for the Uncertainty Estimation in Stereo Vision , 2011, IEEE Transactions on Instrumentation and Measurement.

[6]  Antonio Pietrosanto,et al.  Structured approach to estimate the measurement uncertainty in digital signal elaboration algorithms , 1999 .

[7]  Andrew Zisserman,et al.  Multiple View Geometry in Computer Vision (2nd ed) , 2003 .

[8]  C. Liguori,et al.  Propagation of uncertainty through stereo triangulation , 2010, 2010 IEEE Instrumentation & Measurement Technology Conference Proceedings.

[9]  O. Faugeras.  Three-dimensional computer vision: a geometric viewpoint , 1993 .

[10]  Jiechun Chen,et al.  Theoretical Uncertainty Evaluation of Stereo Reconstruction , 2008, 2008 2nd International Conference on Bioinformatics and Biomedical Engineering.

[11]  Kenichi Kanatani,et al.  Triangulation from Two Views Revisited: Hartley-Sturm vs. Optimal Correction , 2008, BMVC.

[12]  Robert M. Haralick.  Propagating covariance in computer vision , 1994, Proceedings of 12th International Conference on Pattern Recognition.

[13]  Alexandru Tupan,et al.  Triangulation , 1997, Comput. Vis. Image Underst..

[14]  Janne Heikkilä,et al.  A four-step camera calibration procedure with implicit image correction , 1997, Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition.