Abstract

For stereoscopic systems designed for metrology applications, the accuracy of camera calibration dictates the precision of the 3D reconstruction. In this paper, the impact of various calibration conditions on the reconstruction quality is studied using a virtual camera calibration technique and the design file of a commercially available lens. This technique enables the study of the statistical behavior of the reconstruction task in selected calibration conditions. The data show that the mean reprojection error should not always be used to evaluate the performance of the calibration process and that a low quality of feature detection does not always lead to a high mean reconstruction error.

© 2016 Optical Society of America

Full Article  |  PDF Article
OSA Recommended Articles
Virtual camera calibration using optical design software

Anne-Sophie Poulin-Girard, Xavier Dallaire, Simon Thibault, and Denis Laurendeau
Appl. Opt. 53(13) 2822-2827 (2014)

Pre-calibration-free 3D shape measurement method based on fringe projection

Kai Zhong, Zhongwei Li, Renfu Li, Yusheng Shi, and Congjun Wang
Opt. Express 24(13) 14196-14207 (2016)

Flexible calibration method for telecentric fringe projection profilometry systems

Li Rao, Feipeng Da, Weiqi Kong, and Heming Huang
Opt. Express 24(2) 1222-1237 (2016)

References

  • View by:
  • |
  • |
  • |

  1. M. Nekouei Shahraki and N. Haala, “Introducing free-function camera calibration model for central-projection and omni-directional lenses,” Proc. SPIE 9630, 96300P (2015).
  2. Y. Hueng, G. Ren, and E. Liu, “Non-iterative method for camera calibration,” Opt. Express 23(18), 246365 (2015).
  3. Z. Wang, “Removal of noise and radial lens distortion during calibration of computer vision systems,” Opt. Express 23(9), 234340 (2015).
  4. J. Salvi, X. Armangué, and J. Batlle, “A Comparative review of camera calibrating methods with accuracy evaluation,” Pattern Recognit. 35(7), 1617–1635 (2002).
    [Crossref]
  5. P. D. Lin and C. K. Sung, “Comparing two new camera calibration methods with traditional pinhole calibrations,” Opt. Express 15(6), 3012–3022 (2007).
    [Crossref] [PubMed]
  6. W. Sun and J. R. Cooperstock, “Requirements for Camera Calibration: Must Accuracy Come with a High Price,” in Proceedings of the Seventh IEEE Workshop on Applications of Computer Vision (IEEE, 2005), pp. 356–361.
  7. P. Swapna, N. Krouglicof, and R. Gosine, “The question of accuracy with geometric camera calibration,” in Proceedings of the Seventh IEEE Canadian Conference on Electrical and Computer Engineering (IEEE, 2009), pp. 541–546.
  8. W. Sun and J. R. Cooperstock, “An empirical evaluation of factors influencing camera calibration accuracy using three publicly available techniques,” Mach. Vis. Appl. 17(1), 51–67 (2006).
    [Crossref]
  9. M. F.A.l Hassan, I. Ma’arof, and A. M. Samad, “Assessment of Camera Calibration Towards Accuracy Requirement,” in Proceedings of IEEE 10th International Colloquium on Signal Processing and its Applications (IEEE, 2014), pp. 123–128.
  10. T. Hanning, S. Graf, and M. Kellner, “Re-projective vs. projective camera calibration: effects on 3D-reconstruction,” in Proceedings of IEEE International Conference on Image Processing (IEEE, 2005), pp. II–1170.
  11. Z. Zhang, “Flexible camera calibration by viewing a plane from unknown orientations,” in Proceedings of the Seventh IEEE International Conference on Computer Vision, (IEEE, 1999), vol.1, pp. 666–673.
  12. C. Ricolfe-Viala and A.-J. Sanchez-Salmeron, “Camera calibration under optimal conditions,” Opt. Express 19(11), 10769–10775 (2011).
    [Crossref] [PubMed]
  13. A.-S. Poulin-Girard, X. Dallaire, S. Thibault, and D. Laurendeau, “Virtual camera calibration using optical design software,” Appl. Opt. 53(13), 2822–2827 (2014).
    [Crossref] [PubMed]
  14. J.-Y. Bouguet, “Camera Calibration Toolbox for Matlab,” http://www.vision.caltech.edu/bouguetj/calib_doc/index.html .
  15. J. Heikkila and O. Silvén, “A four-step camera calibration procedure with implicit image correction,” in Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition (IEEE, 1997), pp. 1106–1112.
  16. Z. Zhang, “A flexible new technique for camera calibration,” IEEE Trans. Pattern Recognit. Mach. Intell. 22(11), 1330–1334 (2000).
    [Crossref]
  17. A.-S. Poulin-Girard, X. Dallaire, A. Veillette, S. Thibault, and D. Laurendeau, “Study of Camera Calibration Process with Ray Tracing,” Proc. SPIE 9192, 91920B (2014).
    [Crossref]
  18. D. Griffith, “How to Talk to Zemax from MATLAB” (Zemax Corporation, 2006). http://www.zemax.com/support/resource-center/knowledgebase/how-to-talk-to-zemax-from-matlab

2015 (3)

M. Nekouei Shahraki and N. Haala, “Introducing free-function camera calibration model for central-projection and omni-directional lenses,” Proc. SPIE 9630, 96300P (2015).

Y. Hueng, G. Ren, and E. Liu, “Non-iterative method for camera calibration,” Opt. Express 23(18), 246365 (2015).

Z. Wang, “Removal of noise and radial lens distortion during calibration of computer vision systems,” Opt. Express 23(9), 234340 (2015).

2014 (2)

A.-S. Poulin-Girard, X. Dallaire, S. Thibault, and D. Laurendeau, “Virtual camera calibration using optical design software,” Appl. Opt. 53(13), 2822–2827 (2014).
[Crossref] [PubMed]

A.-S. Poulin-Girard, X. Dallaire, A. Veillette, S. Thibault, and D. Laurendeau, “Study of Camera Calibration Process with Ray Tracing,” Proc. SPIE 9192, 91920B (2014).
[Crossref]

2011 (1)

2007 (1)

2006 (1)

W. Sun and J. R. Cooperstock, “An empirical evaluation of factors influencing camera calibration accuracy using three publicly available techniques,” Mach. Vis. Appl. 17(1), 51–67 (2006).
[Crossref]

2002 (1)

J. Salvi, X. Armangué, and J. Batlle, “A Comparative review of camera calibrating methods with accuracy evaluation,” Pattern Recognit. 35(7), 1617–1635 (2002).
[Crossref]

2000 (1)

Z. Zhang, “A flexible new technique for camera calibration,” IEEE Trans. Pattern Recognit. Mach. Intell. 22(11), 1330–1334 (2000).
[Crossref]

Armangué, X.

J. Salvi, X. Armangué, and J. Batlle, “A Comparative review of camera calibrating methods with accuracy evaluation,” Pattern Recognit. 35(7), 1617–1635 (2002).
[Crossref]

Batlle, J.

J. Salvi, X. Armangué, and J. Batlle, “A Comparative review of camera calibrating methods with accuracy evaluation,” Pattern Recognit. 35(7), 1617–1635 (2002).
[Crossref]

Cooperstock, J. R.

W. Sun and J. R. Cooperstock, “An empirical evaluation of factors influencing camera calibration accuracy using three publicly available techniques,” Mach. Vis. Appl. 17(1), 51–67 (2006).
[Crossref]

W. Sun and J. R. Cooperstock, “Requirements for Camera Calibration: Must Accuracy Come with a High Price,” in Proceedings of the Seventh IEEE Workshop on Applications of Computer Vision (IEEE, 2005), pp. 356–361.

Dallaire, X.

A.-S. Poulin-Girard, X. Dallaire, A. Veillette, S. Thibault, and D. Laurendeau, “Study of Camera Calibration Process with Ray Tracing,” Proc. SPIE 9192, 91920B (2014).
[Crossref]

A.-S. Poulin-Girard, X. Dallaire, S. Thibault, and D. Laurendeau, “Virtual camera calibration using optical design software,” Appl. Opt. 53(13), 2822–2827 (2014).
[Crossref] [PubMed]

Gosine, R.

P. Swapna, N. Krouglicof, and R. Gosine, “The question of accuracy with geometric camera calibration,” in Proceedings of the Seventh IEEE Canadian Conference on Electrical and Computer Engineering (IEEE, 2009), pp. 541–546.

Graf, S.

T. Hanning, S. Graf, and M. Kellner, “Re-projective vs. projective camera calibration: effects on 3D-reconstruction,” in Proceedings of IEEE International Conference on Image Processing (IEEE, 2005), pp. II–1170.

Griffith, D.

D. Griffith, “How to Talk to Zemax from MATLAB” (Zemax Corporation, 2006). http://www.zemax.com/support/resource-center/knowledgebase/how-to-talk-to-zemax-from-matlab

Haala, N.

M. Nekouei Shahraki and N. Haala, “Introducing free-function camera calibration model for central-projection and omni-directional lenses,” Proc. SPIE 9630, 96300P (2015).

Hanning, T.

T. Hanning, S. Graf, and M. Kellner, “Re-projective vs. projective camera calibration: effects on 3D-reconstruction,” in Proceedings of IEEE International Conference on Image Processing (IEEE, 2005), pp. II–1170.

Hassan, M. F.A.l

M. F.A.l Hassan, I. Ma’arof, and A. M. Samad, “Assessment of Camera Calibration Towards Accuracy Requirement,” in Proceedings of IEEE 10th International Colloquium on Signal Processing and its Applications (IEEE, 2014), pp. 123–128.

Heikkila, J.

J. Heikkila and O. Silvén, “A four-step camera calibration procedure with implicit image correction,” in Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition (IEEE, 1997), pp. 1106–1112.

Hueng, Y.

Y. Hueng, G. Ren, and E. Liu, “Non-iterative method for camera calibration,” Opt. Express 23(18), 246365 (2015).

Kellner, M.

T. Hanning, S. Graf, and M. Kellner, “Re-projective vs. projective camera calibration: effects on 3D-reconstruction,” in Proceedings of IEEE International Conference on Image Processing (IEEE, 2005), pp. II–1170.

Krouglicof, N.

P. Swapna, N. Krouglicof, and R. Gosine, “The question of accuracy with geometric camera calibration,” in Proceedings of the Seventh IEEE Canadian Conference on Electrical and Computer Engineering (IEEE, 2009), pp. 541–546.

Laurendeau, D.

A.-S. Poulin-Girard, X. Dallaire, A. Veillette, S. Thibault, and D. Laurendeau, “Study of Camera Calibration Process with Ray Tracing,” Proc. SPIE 9192, 91920B (2014).
[Crossref]

A.-S. Poulin-Girard, X. Dallaire, S. Thibault, and D. Laurendeau, “Virtual camera calibration using optical design software,” Appl. Opt. 53(13), 2822–2827 (2014).
[Crossref] [PubMed]

Lin, P. D.

Liu, E.

Y. Hueng, G. Ren, and E. Liu, “Non-iterative method for camera calibration,” Opt. Express 23(18), 246365 (2015).

Ma’arof, I.

M. F.A.l Hassan, I. Ma’arof, and A. M. Samad, “Assessment of Camera Calibration Towards Accuracy Requirement,” in Proceedings of IEEE 10th International Colloquium on Signal Processing and its Applications (IEEE, 2014), pp. 123–128.

Nekouei Shahraki, M.

M. Nekouei Shahraki and N. Haala, “Introducing free-function camera calibration model for central-projection and omni-directional lenses,” Proc. SPIE 9630, 96300P (2015).

Poulin-Girard, A.-S.

A.-S. Poulin-Girard, X. Dallaire, A. Veillette, S. Thibault, and D. Laurendeau, “Study of Camera Calibration Process with Ray Tracing,” Proc. SPIE 9192, 91920B (2014).
[Crossref]

A.-S. Poulin-Girard, X. Dallaire, S. Thibault, and D. Laurendeau, “Virtual camera calibration using optical design software,” Appl. Opt. 53(13), 2822–2827 (2014).
[Crossref] [PubMed]

Ren, G.

Y. Hueng, G. Ren, and E. Liu, “Non-iterative method for camera calibration,” Opt. Express 23(18), 246365 (2015).

Ricolfe-Viala, C.

Salvi, J.

J. Salvi, X. Armangué, and J. Batlle, “A Comparative review of camera calibrating methods with accuracy evaluation,” Pattern Recognit. 35(7), 1617–1635 (2002).
[Crossref]

Samad, A. M.

M. F.A.l Hassan, I. Ma’arof, and A. M. Samad, “Assessment of Camera Calibration Towards Accuracy Requirement,” in Proceedings of IEEE 10th International Colloquium on Signal Processing and its Applications (IEEE, 2014), pp. 123–128.

Sanchez-Salmeron, A.-J.

Silvén, O.

J. Heikkila and O. Silvén, “A four-step camera calibration procedure with implicit image correction,” in Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition (IEEE, 1997), pp. 1106–1112.

Sun, W.

W. Sun and J. R. Cooperstock, “An empirical evaluation of factors influencing camera calibration accuracy using three publicly available techniques,” Mach. Vis. Appl. 17(1), 51–67 (2006).
[Crossref]

W. Sun and J. R. Cooperstock, “Requirements for Camera Calibration: Must Accuracy Come with a High Price,” in Proceedings of the Seventh IEEE Workshop on Applications of Computer Vision (IEEE, 2005), pp. 356–361.

Sung, C. K.

Swapna, P.

P. Swapna, N. Krouglicof, and R. Gosine, “The question of accuracy with geometric camera calibration,” in Proceedings of the Seventh IEEE Canadian Conference on Electrical and Computer Engineering (IEEE, 2009), pp. 541–546.

Thibault, S.

A.-S. Poulin-Girard, X. Dallaire, A. Veillette, S. Thibault, and D. Laurendeau, “Study of Camera Calibration Process with Ray Tracing,” Proc. SPIE 9192, 91920B (2014).
[Crossref]

A.-S. Poulin-Girard, X. Dallaire, S. Thibault, and D. Laurendeau, “Virtual camera calibration using optical design software,” Appl. Opt. 53(13), 2822–2827 (2014).
[Crossref] [PubMed]

Veillette, A.

A.-S. Poulin-Girard, X. Dallaire, A. Veillette, S. Thibault, and D. Laurendeau, “Study of Camera Calibration Process with Ray Tracing,” Proc. SPIE 9192, 91920B (2014).
[Crossref]

Wang, Z.

Z. Wang, “Removal of noise and radial lens distortion during calibration of computer vision systems,” Opt. Express 23(9), 234340 (2015).

Zhang, Z.

Z. Zhang, “A flexible new technique for camera calibration,” IEEE Trans. Pattern Recognit. Mach. Intell. 22(11), 1330–1334 (2000).
[Crossref]

Z. Zhang, “Flexible camera calibration by viewing a plane from unknown orientations,” in Proceedings of the Seventh IEEE International Conference on Computer Vision, (IEEE, 1999), vol.1, pp. 666–673.

Appl. Opt. (1)

IEEE Trans. Pattern Recognit. Mach. Intell. (1)

Z. Zhang, “A flexible new technique for camera calibration,” IEEE Trans. Pattern Recognit. Mach. Intell. 22(11), 1330–1334 (2000).
[Crossref]

Mach. Vis. Appl. (1)

W. Sun and J. R. Cooperstock, “An empirical evaluation of factors influencing camera calibration accuracy using three publicly available techniques,” Mach. Vis. Appl. 17(1), 51–67 (2006).
[Crossref]

Opt. Express (4)

Y. Hueng, G. Ren, and E. Liu, “Non-iterative method for camera calibration,” Opt. Express 23(18), 246365 (2015).

Z. Wang, “Removal of noise and radial lens distortion during calibration of computer vision systems,” Opt. Express 23(9), 234340 (2015).

P. D. Lin and C. K. Sung, “Comparing two new camera calibration methods with traditional pinhole calibrations,” Opt. Express 15(6), 3012–3022 (2007).
[Crossref] [PubMed]

C. Ricolfe-Viala and A.-J. Sanchez-Salmeron, “Camera calibration under optimal conditions,” Opt. Express 19(11), 10769–10775 (2011).
[Crossref] [PubMed]

Pattern Recognit. (1)

J. Salvi, X. Armangué, and J. Batlle, “A Comparative review of camera calibrating methods with accuracy evaluation,” Pattern Recognit. 35(7), 1617–1635 (2002).
[Crossref]

Proc. SPIE (2)

M. Nekouei Shahraki and N. Haala, “Introducing free-function camera calibration model for central-projection and omni-directional lenses,” Proc. SPIE 9630, 96300P (2015).

A.-S. Poulin-Girard, X. Dallaire, A. Veillette, S. Thibault, and D. Laurendeau, “Study of Camera Calibration Process with Ray Tracing,” Proc. SPIE 9192, 91920B (2014).
[Crossref]

Other (8)

D. Griffith, “How to Talk to Zemax from MATLAB” (Zemax Corporation, 2006). http://www.zemax.com/support/resource-center/knowledgebase/how-to-talk-to-zemax-from-matlab

J.-Y. Bouguet, “Camera Calibration Toolbox for Matlab,” http://www.vision.caltech.edu/bouguetj/calib_doc/index.html .

J. Heikkila and O. Silvén, “A four-step camera calibration procedure with implicit image correction,” in Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition (IEEE, 1997), pp. 1106–1112.

W. Sun and J. R. Cooperstock, “Requirements for Camera Calibration: Must Accuracy Come with a High Price,” in Proceedings of the Seventh IEEE Workshop on Applications of Computer Vision (IEEE, 2005), pp. 356–361.

P. Swapna, N. Krouglicof, and R. Gosine, “The question of accuracy with geometric camera calibration,” in Proceedings of the Seventh IEEE Canadian Conference on Electrical and Computer Engineering (IEEE, 2009), pp. 541–546.

M. F.A.l Hassan, I. Ma’arof, and A. M. Samad, “Assessment of Camera Calibration Towards Accuracy Requirement,” in Proceedings of IEEE 10th International Colloquium on Signal Processing and its Applications (IEEE, 2014), pp. 123–128.

T. Hanning, S. Graf, and M. Kellner, “Re-projective vs. projective camera calibration: effects on 3D-reconstruction,” in Proceedings of IEEE International Conference on Image Processing (IEEE, 2005), pp. II–1170.

Z. Zhang, “Flexible camera calibration by viewing a plane from unknown orientations,” in Proceedings of the Seventh IEEE International Conference on Computer Vision, (IEEE, 1999), vol.1, pp. 666–673.

Cited By

OSA participates in Crossref's Cited-By Linking service. Citing articles from OSA journals and other participating publishers are listed here.

Alert me when this article is cited.


Figures (2)

Fig. 1
Fig. 1

Flow chart of the virtual calibration technique using a camera calibration toolbox and the optical software Zemax

Fig. 2
Fig. 2

Positions of the calibration target in object space. Positions with identical symbols are located at the same distance z. The black circle and its coordinate system indicate the location and orientation of the camera. The optical axis is oriented along the z axis.

Tables (3)

Tables Icon

Table 1 Statistical mean reconstruction error of the volume of interest for 20 different calibration runs as a function of the number of targets per position. The results are shown for two values of the pixel pitch that represents the quality of the detection of the control points.

Tables Icon

Table 2 Statistical mean reconstruction error of the volume of interest for 20 different calibration runs as a function of the density of control points on the calibration target. The results are shown for two values of the pixel pitch that represents the quality of the detection of the control points.

Tables Icon

Table 3 Mean reconstruction error for the volume of interest and mean reprojection error of the calibration process for 20 different calibrations. The calibration conditions are the following: a pixel pitch of 6.6 μm, a target density of one target per position and a density of control points of 10 points/meter.

Equations (3)

Equations on this page are rendered with MathJax. Learn more.

p n = [ x n y n ] = [ X / Z Y / Z ]
p d = [ x d y d ] = ( 1 + k 1 r n 2 + k 2 r n 4 + k 5 r n 6 ) [ x n y n ] + [ 2 k 3 x n y n + k 4 ( r n 2 + 2 x n 2 ) k 3 ( r n 2 + 2 y n 2 ) + 2 k 4 x n y n ]
[ x p y p 1 ] = [ f c x 0 c c x 0 f c y c c y 0 0 1 ] K K [ x p y p 1 ]

Metrics