Abstract

We propose an easy-to-implement yet accurate calibration method for large-scale 3D measurements that makes use of a regular-sized phase target and two planar mirrors. Being insensitive to severe defocus, the phase target is placed as to span a large depth within the field of view (FOV) of each camera for accurate intrinsic calibration. Extrinsic calibration is achieved by placing the phase target in the FOV of a short-range virtual stereo-system generated by the mirrors. Results from 3D shape and deformation measurements demonstrate that the proposed method is capable to operate within a working volume of 3 m × 2 m × 1.8 m with an error < 0.1% of the FOV thus opening to new possibilities for large-scale measurements in mechanical and civil engineering applications.

© 2019 Optical Society of America under the terms of the OSA Open Access Publishing Agreement

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References

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  1. M. A. Sutton, J. J. Orteu, and H. Schreier, Image correlation for shape, motion and deformation measurements: basic concepts, theory and applications (Springer Science & Business Media, 2009).
  2. B. Pan, “Digital image correlation for surface deformation measurement: historical developments, recent advances and future goals,” Meas. Sci. Technol. 29(8), 082001 (2018).
    [Crossref]
  3. B. Pan, K. Qian, H. Xie, and A. Asundi, “Two-dimensional digital image correlation for in-plane displacement and strain measurement: a review,” Meas. Sci. Technol. 20(6), 062001 (2009).
    [Crossref]
  4. R. Ghorbani, F. Matta, and M. A. Sutton, “Full-field deformation measurement and crack mapping on confined masonry walls using digital image correlation,” Exp. Mech. 55(1), 227–243 (2015).
    [Crossref]
  5. M. Sutton, F. Matta, D. Rizos, R. Ghorbani, S. Rajan, D. Mollenhauer, H. Schreier, and A. Lasprilla, “Recent progress in digital image correlation: background and developments since the 2013 Murray lecture,” Exp. Mech. 57(1), 1–30 (2017).
    [Crossref]
  6. X. Shao, X. Dai, Z. Chen, Y. Dai, S. Dong, and X. He, “Calibration of stereo-digital image correlation for deformation measurement of large engineering components,” Meas. Sci. Technol. 27(12), 125010 (2016).
    [Crossref]
  7. Z. Zhang, “A flexible new technique for camera calibration,” IEEE Trans. Pattern Anal. Mach. Intell. 22(11), 1330–1334 (2000).
    [Crossref]
  8. R. Tsai, “A versatile camera calibration technique for high-accuracy 3d machine vision metrology using off-the-shelf tv cameras and lenses,” IEEE J. Robot. Autom. 3(4), 323–344 (1987).
    [Crossref]
  9. C. Schmalz, F. Forster, and E. Angelopoulou, “Camera calibration: active versus passive targets,” Opt. Eng. 50(11), 113601 (2011).
    [Crossref]
  10. L. Huang, Q. Zhang, and A. Asundi, “Camera calibration with active phase target: improvement on feature detection and optimization,” Opt. Lett. 38(9), 1446–1448 (2013).
    [Crossref] [PubMed]
  11. Y. An, T. Bell, B. Li, J. Xu, and S. Zhang, “Method for large-range structured light system calibration,” Appl. Opt. 55(33), 9563–9572 (2016).
    [Crossref] [PubMed]
  12. T. Bell, J. Xu, and S. Zhang, “Method for out-of-focus camera calibration,” Appl. Opt. 55(9), 2346–2352 (2016).
    [Crossref] [PubMed]
  13. S. S. Gorthi and P. Rastogi, “Fringe projection techniques: whither we are?” Opt. Lasers Eng. 48(2), 133–140 (2010).
    [Crossref]
  14. P. Wang, J. Wang, J. Xu, Y. Guan, G. Zhang, and K. Chen, “Calibration method for a large-scale structured light measurement system,” Appl. Opt. 56(14), 3995–4002 (2017).
    [Crossref] [PubMed]
  15. B. Li, N. Karpinsky, and S. Zhang, “Novel calibration method for structured-light system with an out-of-focus projector,” Appl. Opt. 53(16), 3415–3426 (2014).
    [Crossref] [PubMed]
  16. K. Takahashi and S. Nobuhara, andT.Matsuyama, “A new mirror-based extrinsic camera calibration using an orthogonality constraint,” in 2012 IEEE Conference on Computer Vision and Pattern Recognition, (IEEE, 2012), pp. 1051–1058.
    [Crossref]
  17. J. A. Hesch, A. I. Mourikis, and S. I. Roumeliotis, “Mirror-based extrinsic camera calibration,” in Algorithmic Foundation of Robotics VIII, (Springer, 2009), pp. 285–299.
  18. R. K. Kumar, A. Ilie, J.-M. Frahm, and M. Pollefeys, “Simple calibration of non-overlapping cameras with a mirror,” in Computer Vision and Pattern Recognition,2008. CVPR 2008. IEEE Conference on, (IEEE, 2008), pp. 1–7.
    [Crossref]
  19. J. Heikkila and O. Silven, “A four-step camera calibration procedure with implicit image correction,” Computer Vision and Pattern Recognition,1997. CVPR 1997. IEEE Conference on, (IEEE, 1997),1106–1112.
    [Crossref]
  20. F. Sur, B. Blaysat, and M. Grediac, “Rendering deformed speckle images with a boolean model,” J. Math. Imaging Vis. 60, 1–17 (2017).

2018 (1)

B. Pan, “Digital image correlation for surface deformation measurement: historical developments, recent advances and future goals,” Meas. Sci. Technol. 29(8), 082001 (2018).
[Crossref]

2017 (3)

M. Sutton, F. Matta, D. Rizos, R. Ghorbani, S. Rajan, D. Mollenhauer, H. Schreier, and A. Lasprilla, “Recent progress in digital image correlation: background and developments since the 2013 Murray lecture,” Exp. Mech. 57(1), 1–30 (2017).
[Crossref]

P. Wang, J. Wang, J. Xu, Y. Guan, G. Zhang, and K. Chen, “Calibration method for a large-scale structured light measurement system,” Appl. Opt. 56(14), 3995–4002 (2017).
[Crossref] [PubMed]

F. Sur, B. Blaysat, and M. Grediac, “Rendering deformed speckle images with a boolean model,” J. Math. Imaging Vis. 60, 1–17 (2017).

2016 (3)

Y. An, T. Bell, B. Li, J. Xu, and S. Zhang, “Method for large-range structured light system calibration,” Appl. Opt. 55(33), 9563–9572 (2016).
[Crossref] [PubMed]

T. Bell, J. Xu, and S. Zhang, “Method for out-of-focus camera calibration,” Appl. Opt. 55(9), 2346–2352 (2016).
[Crossref] [PubMed]

X. Shao, X. Dai, Z. Chen, Y. Dai, S. Dong, and X. He, “Calibration of stereo-digital image correlation for deformation measurement of large engineering components,” Meas. Sci. Technol. 27(12), 125010 (2016).
[Crossref]

2015 (1)

R. Ghorbani, F. Matta, and M. A. Sutton, “Full-field deformation measurement and crack mapping on confined masonry walls using digital image correlation,” Exp. Mech. 55(1), 227–243 (2015).
[Crossref]

2014 (1)

B. Li, N. Karpinsky, and S. Zhang, “Novel calibration method for structured-light system with an out-of-focus projector,” Appl. Opt. 53(16), 3415–3426 (2014).
[Crossref] [PubMed]

2013 (1)

L. Huang, Q. Zhang, and A. Asundi, “Camera calibration with active phase target: improvement on feature detection and optimization,” Opt. Lett. 38(9), 1446–1448 (2013).
[Crossref] [PubMed]

2011 (1)

C. Schmalz, F. Forster, and E. Angelopoulou, “Camera calibration: active versus passive targets,” Opt. Eng. 50(11), 113601 (2011).
[Crossref]

2010 (1)

S. S. Gorthi and P. Rastogi, “Fringe projection techniques: whither we are?” Opt. Lasers Eng. 48(2), 133–140 (2010).
[Crossref]

2009 (1)

B. Pan, K. Qian, H. Xie, and A. Asundi, “Two-dimensional digital image correlation for in-plane displacement and strain measurement: a review,” Meas. Sci. Technol. 20(6), 062001 (2009).
[Crossref]

2000 (1)

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

1987 (1)

R. Tsai, “A versatile camera calibration technique for high-accuracy 3d machine vision metrology using off-the-shelf tv cameras and lenses,” IEEE J. Robot. Autom. 3(4), 323–344 (1987).
[Crossref]

An, Y.

Y. An, T. Bell, B. Li, J. Xu, and S. Zhang, “Method for large-range structured light system calibration,” Appl. Opt. 55(33), 9563–9572 (2016).
[Crossref] [PubMed]

Angelopoulou, E.

C. Schmalz, F. Forster, and E. Angelopoulou, “Camera calibration: active versus passive targets,” Opt. Eng. 50(11), 113601 (2011).
[Crossref]

Asundi, A.

L. Huang, Q. Zhang, and A. Asundi, “Camera calibration with active phase target: improvement on feature detection and optimization,” Opt. Lett. 38(9), 1446–1448 (2013).
[Crossref] [PubMed]

B. Pan, K. Qian, H. Xie, and A. Asundi, “Two-dimensional digital image correlation for in-plane displacement and strain measurement: a review,” Meas. Sci. Technol. 20(6), 062001 (2009).
[Crossref]

Bell, T.

Y. An, T. Bell, B. Li, J. Xu, and S. Zhang, “Method for large-range structured light system calibration,” Appl. Opt. 55(33), 9563–9572 (2016).
[Crossref] [PubMed]

T. Bell, J. Xu, and S. Zhang, “Method for out-of-focus camera calibration,” Appl. Opt. 55(9), 2346–2352 (2016).
[Crossref] [PubMed]

Blaysat, B.

F. Sur, B. Blaysat, and M. Grediac, “Rendering deformed speckle images with a boolean model,” J. Math. Imaging Vis. 60, 1–17 (2017).

Chen, K.

P. Wang, J. Wang, J. Xu, Y. Guan, G. Zhang, and K. Chen, “Calibration method for a large-scale structured light measurement system,” Appl. Opt. 56(14), 3995–4002 (2017).
[Crossref] [PubMed]

Chen, Z.

X. Shao, X. Dai, Z. Chen, Y. Dai, S. Dong, and X. He, “Calibration of stereo-digital image correlation for deformation measurement of large engineering components,” Meas. Sci. Technol. 27(12), 125010 (2016).
[Crossref]

Dai, X.

X. Shao, X. Dai, Z. Chen, Y. Dai, S. Dong, and X. He, “Calibration of stereo-digital image correlation for deformation measurement of large engineering components,” Meas. Sci. Technol. 27(12), 125010 (2016).
[Crossref]

Dai, Y.

X. Shao, X. Dai, Z. Chen, Y. Dai, S. Dong, and X. He, “Calibration of stereo-digital image correlation for deformation measurement of large engineering components,” Meas. Sci. Technol. 27(12), 125010 (2016).
[Crossref]

Dong, S.

X. Shao, X. Dai, Z. Chen, Y. Dai, S. Dong, and X. He, “Calibration of stereo-digital image correlation for deformation measurement of large engineering components,” Meas. Sci. Technol. 27(12), 125010 (2016).
[Crossref]

Forster, F.

C. Schmalz, F. Forster, and E. Angelopoulou, “Camera calibration: active versus passive targets,” Opt. Eng. 50(11), 113601 (2011).
[Crossref]

Ghorbani, R.

M. Sutton, F. Matta, D. Rizos, R. Ghorbani, S. Rajan, D. Mollenhauer, H. Schreier, and A. Lasprilla, “Recent progress in digital image correlation: background and developments since the 2013 Murray lecture,” Exp. Mech. 57(1), 1–30 (2017).
[Crossref]

R. Ghorbani, F. Matta, and M. A. Sutton, “Full-field deformation measurement and crack mapping on confined masonry walls using digital image correlation,” Exp. Mech. 55(1), 227–243 (2015).
[Crossref]

Gorthi, S. S.

S. S. Gorthi and P. Rastogi, “Fringe projection techniques: whither we are?” Opt. Lasers Eng. 48(2), 133–140 (2010).
[Crossref]

Grediac, M.

F. Sur, B. Blaysat, and M. Grediac, “Rendering deformed speckle images with a boolean model,” J. Math. Imaging Vis. 60, 1–17 (2017).

Guan, Y.

P. Wang, J. Wang, J. Xu, Y. Guan, G. Zhang, and K. Chen, “Calibration method for a large-scale structured light measurement system,” Appl. Opt. 56(14), 3995–4002 (2017).
[Crossref] [PubMed]

He, X.

X. Shao, X. Dai, Z. Chen, Y. Dai, S. Dong, and X. He, “Calibration of stereo-digital image correlation for deformation measurement of large engineering components,” Meas. Sci. Technol. 27(12), 125010 (2016).
[Crossref]

Huang, L.

L. Huang, Q. Zhang, and A. Asundi, “Camera calibration with active phase target: improvement on feature detection and optimization,” Opt. Lett. 38(9), 1446–1448 (2013).
[Crossref] [PubMed]

Karpinsky, N.

B. Li, N. Karpinsky, and S. Zhang, “Novel calibration method for structured-light system with an out-of-focus projector,” Appl. Opt. 53(16), 3415–3426 (2014).
[Crossref] [PubMed]

Lasprilla, A.

M. Sutton, F. Matta, D. Rizos, R. Ghorbani, S. Rajan, D. Mollenhauer, H. Schreier, and A. Lasprilla, “Recent progress in digital image correlation: background and developments since the 2013 Murray lecture,” Exp. Mech. 57(1), 1–30 (2017).
[Crossref]

Li, B.

Y. An, T. Bell, B. Li, J. Xu, and S. Zhang, “Method for large-range structured light system calibration,” Appl. Opt. 55(33), 9563–9572 (2016).
[Crossref] [PubMed]

B. Li, N. Karpinsky, and S. Zhang, “Novel calibration method for structured-light system with an out-of-focus projector,” Appl. Opt. 53(16), 3415–3426 (2014).
[Crossref] [PubMed]

Matta, F.

M. Sutton, F. Matta, D. Rizos, R. Ghorbani, S. Rajan, D. Mollenhauer, H. Schreier, and A. Lasprilla, “Recent progress in digital image correlation: background and developments since the 2013 Murray lecture,” Exp. Mech. 57(1), 1–30 (2017).
[Crossref]

R. Ghorbani, F. Matta, and M. A. Sutton, “Full-field deformation measurement and crack mapping on confined masonry walls using digital image correlation,” Exp. Mech. 55(1), 227–243 (2015).
[Crossref]

Mollenhauer, D.

M. Sutton, F. Matta, D. Rizos, R. Ghorbani, S. Rajan, D. Mollenhauer, H. Schreier, and A. Lasprilla, “Recent progress in digital image correlation: background and developments since the 2013 Murray lecture,” Exp. Mech. 57(1), 1–30 (2017).
[Crossref]

Nobuhara, S.

K. Takahashi and S. Nobuhara, andT.Matsuyama, “A new mirror-based extrinsic camera calibration using an orthogonality constraint,” in 2012 IEEE Conference on Computer Vision and Pattern Recognition, (IEEE, 2012), pp. 1051–1058.
[Crossref]

Pan, B.

B. Pan, “Digital image correlation for surface deformation measurement: historical developments, recent advances and future goals,” Meas. Sci. Technol. 29(8), 082001 (2018).
[Crossref]

B. Pan, K. Qian, H. Xie, and A. Asundi, “Two-dimensional digital image correlation for in-plane displacement and strain measurement: a review,” Meas. Sci. Technol. 20(6), 062001 (2009).
[Crossref]

Qian, K.

B. Pan, K. Qian, H. Xie, and A. Asundi, “Two-dimensional digital image correlation for in-plane displacement and strain measurement: a review,” Meas. Sci. Technol. 20(6), 062001 (2009).
[Crossref]

Rajan, S.

M. Sutton, F. Matta, D. Rizos, R. Ghorbani, S. Rajan, D. Mollenhauer, H. Schreier, and A. Lasprilla, “Recent progress in digital image correlation: background and developments since the 2013 Murray lecture,” Exp. Mech. 57(1), 1–30 (2017).
[Crossref]

Rastogi, P.

S. S. Gorthi and P. Rastogi, “Fringe projection techniques: whither we are?” Opt. Lasers Eng. 48(2), 133–140 (2010).
[Crossref]

Rizos, D.

M. Sutton, F. Matta, D. Rizos, R. Ghorbani, S. Rajan, D. Mollenhauer, H. Schreier, and A. Lasprilla, “Recent progress in digital image correlation: background and developments since the 2013 Murray lecture,” Exp. Mech. 57(1), 1–30 (2017).
[Crossref]

Schmalz, C.

C. Schmalz, F. Forster, and E. Angelopoulou, “Camera calibration: active versus passive targets,” Opt. Eng. 50(11), 113601 (2011).
[Crossref]

Schreier, H.

M. Sutton, F. Matta, D. Rizos, R. Ghorbani, S. Rajan, D. Mollenhauer, H. Schreier, and A. Lasprilla, “Recent progress in digital image correlation: background and developments since the 2013 Murray lecture,” Exp. Mech. 57(1), 1–30 (2017).
[Crossref]

Shao, X.

X. Shao, X. Dai, Z. Chen, Y. Dai, S. Dong, and X. He, “Calibration of stereo-digital image correlation for deformation measurement of large engineering components,” Meas. Sci. Technol. 27(12), 125010 (2016).
[Crossref]

Sur, F.

F. Sur, B. Blaysat, and M. Grediac, “Rendering deformed speckle images with a boolean model,” J. Math. Imaging Vis. 60, 1–17 (2017).

Sutton, M.

M. Sutton, F. Matta, D. Rizos, R. Ghorbani, S. Rajan, D. Mollenhauer, H. Schreier, and A. Lasprilla, “Recent progress in digital image correlation: background and developments since the 2013 Murray lecture,” Exp. Mech. 57(1), 1–30 (2017).
[Crossref]

Sutton, M. A.

R. Ghorbani, F. Matta, and M. A. Sutton, “Full-field deformation measurement and crack mapping on confined masonry walls using digital image correlation,” Exp. Mech. 55(1), 227–243 (2015).
[Crossref]

Takahashi, K.

K. Takahashi and S. Nobuhara, andT.Matsuyama, “A new mirror-based extrinsic camera calibration using an orthogonality constraint,” in 2012 IEEE Conference on Computer Vision and Pattern Recognition, (IEEE, 2012), pp. 1051–1058.
[Crossref]

Tsai, R.

R. Tsai, “A versatile camera calibration technique for high-accuracy 3d machine vision metrology using off-the-shelf tv cameras and lenses,” IEEE J. Robot. Autom. 3(4), 323–344 (1987).
[Crossref]

Wang, J.

P. Wang, J. Wang, J. Xu, Y. Guan, G. Zhang, and K. Chen, “Calibration method for a large-scale structured light measurement system,” Appl. Opt. 56(14), 3995–4002 (2017).
[Crossref] [PubMed]

Wang, P.

P. Wang, J. Wang, J. Xu, Y. Guan, G. Zhang, and K. Chen, “Calibration method for a large-scale structured light measurement system,” Appl. Opt. 56(14), 3995–4002 (2017).
[Crossref] [PubMed]

Xie, H.

B. Pan, K. Qian, H. Xie, and A. Asundi, “Two-dimensional digital image correlation for in-plane displacement and strain measurement: a review,” Meas. Sci. Technol. 20(6), 062001 (2009).
[Crossref]

Xu, J.

P. Wang, J. Wang, J. Xu, Y. Guan, G. Zhang, and K. Chen, “Calibration method for a large-scale structured light measurement system,” Appl. Opt. 56(14), 3995–4002 (2017).
[Crossref] [PubMed]

T. Bell, J. Xu, and S. Zhang, “Method for out-of-focus camera calibration,” Appl. Opt. 55(9), 2346–2352 (2016).
[Crossref] [PubMed]

Y. An, T. Bell, B. Li, J. Xu, and S. Zhang, “Method for large-range structured light system calibration,” Appl. Opt. 55(33), 9563–9572 (2016).
[Crossref] [PubMed]

Zhang, G.

P. Wang, J. Wang, J. Xu, Y. Guan, G. Zhang, and K. Chen, “Calibration method for a large-scale structured light measurement system,” Appl. Opt. 56(14), 3995–4002 (2017).
[Crossref] [PubMed]

Zhang, Q.

L. Huang, Q. Zhang, and A. Asundi, “Camera calibration with active phase target: improvement on feature detection and optimization,” Opt. Lett. 38(9), 1446–1448 (2013).
[Crossref] [PubMed]

Zhang, S.

Y. An, T. Bell, B. Li, J. Xu, and S. Zhang, “Method for large-range structured light system calibration,” Appl. Opt. 55(33), 9563–9572 (2016).
[Crossref] [PubMed]

T. Bell, J. Xu, and S. Zhang, “Method for out-of-focus camera calibration,” Appl. Opt. 55(9), 2346–2352 (2016).
[Crossref] [PubMed]

B. Li, N. Karpinsky, and S. Zhang, “Novel calibration method for structured-light system with an out-of-focus projector,” Appl. Opt. 53(16), 3415–3426 (2014).
[Crossref] [PubMed]

Zhang, Z.

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

Appl. Opt. (4)

P. Wang, J. Wang, J. Xu, Y. Guan, G. Zhang, and K. Chen, “Calibration method for a large-scale structured light measurement system,” Appl. Opt. 56(14), 3995–4002 (2017).
[Crossref] [PubMed]

B. Li, N. Karpinsky, and S. Zhang, “Novel calibration method for structured-light system with an out-of-focus projector,” Appl. Opt. 53(16), 3415–3426 (2014).
[Crossref] [PubMed]

Y. An, T. Bell, B. Li, J. Xu, and S. Zhang, “Method for large-range structured light system calibration,” Appl. Opt. 55(33), 9563–9572 (2016).
[Crossref] [PubMed]

T. Bell, J. Xu, and S. Zhang, “Method for out-of-focus camera calibration,” Appl. Opt. 55(9), 2346–2352 (2016).
[Crossref] [PubMed]

Exp. Mech. (2)

R. Ghorbani, F. Matta, and M. A. Sutton, “Full-field deformation measurement and crack mapping on confined masonry walls using digital image correlation,” Exp. Mech. 55(1), 227–243 (2015).
[Crossref]

M. Sutton, F. Matta, D. Rizos, R. Ghorbani, S. Rajan, D. Mollenhauer, H. Schreier, and A. Lasprilla, “Recent progress in digital image correlation: background and developments since the 2013 Murray lecture,” Exp. Mech. 57(1), 1–30 (2017).
[Crossref]

IEEE J. Robot. Autom. (1)

R. Tsai, “A versatile camera calibration technique for high-accuracy 3d machine vision metrology using off-the-shelf tv cameras and lenses,” IEEE J. Robot. Autom. 3(4), 323–344 (1987).
[Crossref]

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

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

J. Math. Imaging Vis. (1)

F. Sur, B. Blaysat, and M. Grediac, “Rendering deformed speckle images with a boolean model,” J. Math. Imaging Vis. 60, 1–17 (2017).

Meas. Sci. Technol. (3)

X. Shao, X. Dai, Z. Chen, Y. Dai, S. Dong, and X. He, “Calibration of stereo-digital image correlation for deformation measurement of large engineering components,” Meas. Sci. Technol. 27(12), 125010 (2016).
[Crossref]

B. Pan, “Digital image correlation for surface deformation measurement: historical developments, recent advances and future goals,” Meas. Sci. Technol. 29(8), 082001 (2018).
[Crossref]

B. Pan, K. Qian, H. Xie, and A. Asundi, “Two-dimensional digital image correlation for in-plane displacement and strain measurement: a review,” Meas. Sci. Technol. 20(6), 062001 (2009).
[Crossref]

Opt. Eng. (1)

C. Schmalz, F. Forster, and E. Angelopoulou, “Camera calibration: active versus passive targets,” Opt. Eng. 50(11), 113601 (2011).
[Crossref]

Opt. Lasers Eng. (1)

S. S. Gorthi and P. Rastogi, “Fringe projection techniques: whither we are?” Opt. Lasers Eng. 48(2), 133–140 (2010).
[Crossref]

Opt. Lett. (1)

L. Huang, Q. Zhang, and A. Asundi, “Camera calibration with active phase target: improvement on feature detection and optimization,” Opt. Lett. 38(9), 1446–1448 (2013).
[Crossref] [PubMed]

Other (5)

M. A. Sutton, J. J. Orteu, and H. Schreier, Image correlation for shape, motion and deformation measurements: basic concepts, theory and applications (Springer Science & Business Media, 2009).

K. Takahashi and S. Nobuhara, andT.Matsuyama, “A new mirror-based extrinsic camera calibration using an orthogonality constraint,” in 2012 IEEE Conference on Computer Vision and Pattern Recognition, (IEEE, 2012), pp. 1051–1058.
[Crossref]

J. A. Hesch, A. I. Mourikis, and S. I. Roumeliotis, “Mirror-based extrinsic camera calibration,” in Algorithmic Foundation of Robotics VIII, (Springer, 2009), pp. 285–299.

R. K. Kumar, A. Ilie, J.-M. Frahm, and M. Pollefeys, “Simple calibration of non-overlapping cameras with a mirror,” in Computer Vision and Pattern Recognition,2008. CVPR 2008. IEEE Conference on, (IEEE, 2008), pp. 1–7.
[Crossref]

J. Heikkila and O. Silven, “A four-step camera calibration procedure with implicit image correction,” Computer Vision and Pattern Recognition,1997. CVPR 1997. IEEE Conference on, (IEEE, 1997),1106–1112.
[Crossref]

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Figures (11)

Fig. 1
Fig. 1 Schematic of the rationale behind the proposed calibration method for large-scale 3D-DIC measurements. The actual setup having a working distance >> cameras baseline and a V far >> V close is here reported not to scale for the sake of compactness.
Fig. 2
Fig. 2 Picture of the experimental setup during the calibration stage.
Fig. 3
Fig. 3 (a-d) Typical set of phase-shifted sinusoidal patterns as they appear through mirror reflection; (e) corresponding wrapped phase map; (f) computed centroids position. Note the severe blur of the monitor screen due to defocus in the close-range FOV of the virtual stereo-camera system.
Fig. 4
Fig. 4 Schematic of the left camera-mirror-active target layout with the notation used for extrinsic parameters calibration (similarly for the right camera).
Fig. 5
Fig. 5 The sixteen images used for calibrating the left camera. The first three images are the images of the monitor seen through the mirror used to estimate the relative pose of the stereo-cameras. Note the significant difference in magnification of the last two images corresponding to the closest and to the farthest target positions.
Fig. 6
Fig. 6 Results for the left camera calibration plotted in the camera reference system. The insensitivity to defocus of the sinusoidal patterns allowed the calibration target to be placed along a large depth (about 2.5 m) within the FOV of the camera. The farthest position (last frame of Fig. 5) is the closest position in which the monitor is entirely included in the common FOV of the real cameras (Vfar in Fig. 1).
Fig. 7
Fig. 7 Scheme of the layout adopted for evaluating the metrological performances of the long-range stereo-system. The video monitor is sequentially placed in 27 positions arranged in a 3 × 3 × 3 matrix within a working volume of about 3 m × 2 m × 1.8 m. The axes of the cameras cross at the monitor position (2, 2, 2), camera baseline is 1.65 m and working distance is 5.4 m.
Fig. 8
Fig. 8 The 27 positions considered for the dot pattern (upper row) and the speckle pattern (bottom row) at the rear plane (first column), middle plane (second column) and front plane (third column) as seen from the right camera. Each picture is a mosaic of nine cropped images showing only the regions of interest. Note the considerable change in the magnification factor going from the front to the rear plane, and from the left to right side within the same image (the latter due to oblique view).
Fig. 9
Fig. 9 (a) Results for the dot pattern test (see Fig. 8 first row). Color indicates the average distance between the adjacent dots displayed on the screen. The theoretical distance is 139.95 mm while the measured distance for the whole set of points is 139.7 ± 0.46 mm corresponding to a 0.18% error. (b) Results for the speckle pattern test (see Fig. 8 second row). Color indicates the deviation from the best fitting plane. For the entire set of points the calculated deviation from planarity is 0.17 ± 0.038 mm.
Fig. 10
Fig. 10 Results for the deformation test. (a) The undeformed and (b) deformed synthetic images (1800 × 900 pixels) used for display; (c) the captured undeformed image with superimposed the subset (21 × 21 pixels size) and the ROI considered for the analysis (389 × 239 pixels); (d) the measured u deformation map in mm units; (e) the theoretical and experimental deformation vertical profiles in (monitor display) pixels units (1 pixel=0.311 mm); (f) the distribution of residuals between the theoretical and experimental deformation full-field map in (monitor display) pixels units.
Fig. 11
Fig. 11 Illustrative results of a large-scale DIC measurement: (a) the objects layout, (b) the masked ROI with the projected speckle pattern, (c) the reconstructed 3D objects shape with d) corresponding depth map.

Tables (1)

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Table 1 Results for the Displacement Measurement Test

Equations (6)

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p L i = R L p T i + T L
p L i =2( n j T p L j i + d j ) n j + p L j i
( p L 1 i p L 2 i ) T m 12 =0
( ( p L 1 1 p L 2 1 ) T ( p L 1 2 p L 2 2 ) T ( p L 1 3 p L 2 3 ) T ) m 12 = Q 12 m 12 =0.
Q 12 T Q 12 m 12 = M 12 m 12 =0
n 1 = m 12 × m 31 m 12 × m 31 , n 2 = m 23 × m 12 m 23 × m 12 , n 3 = m 31 × m 23 m 31 × m 23 .

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