Abstract

A high-accuracy calibration technique using a white paper and a front coating plane mirror is proposed in this paper for line-structured light vision sensors. This method shows advantages in two aspects. First, a white paper can gain a very high-quality light stripe due to its approximate ideal diffuse Lambertian sheet, which overcomes the problems associated with the strong reflecting light and serious burrs of the light stripe on conventional rigid targets. Second, based on a front coating plane mirror with lithographic feature points, we can obtain a bilateral symmetric structure similar to a virtual binocular stereo vision to recover the 3D coordinates of the light stripe centers on white paper with high accuracy. Front coating guarantees the coplanarity with the lithographic feature points and avoids imaging distortion caused by refraction during back coating. Therefore, front coating can be used to obtain high accuracy structural parameters of the virtual binocular stereo vision sensors. Meanwhile, for the light stripe and its image in the plane mirror are auto-epipolar with all the epipolar lines arranged in parallel. These lines intersect at a vanishing point in the camera image, and this epipolar constraint is used to complete the matching of the light stripe centers without the need for the camera parameters. Experiments are conducted to demonstrate the performance of the proposed method.

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

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References

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    [Crossref]
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    [Crossref]
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    [Crossref]
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    [Crossref]

2016 (1)

2015 (4)

Z. Liu, X. Li, and Y. Yin, “On-site calibration of line-structured light vision sensor in complex light environments,” Opt. Express 23(23), 29896–29911 (2015).
[Crossref]

L. Zhen, X. Li, F. Li, and G. Zhang, “Calibration method for line-structured light vision sensor based on a single ball target,” Opt. Lasers Eng. 69, 20–28 (2015).
[Crossref]

S. Liu, Q. Tan, and Y. Zhang, “Shaft diameter measurement using structured light vision,” Sensors 15(8), 19750–19767 (2015).
[Crossref]

Z. Xu, Y. Wang, and C. Yang, “Multi-camera global calibration for large-scale measurement based on plane mirror,” Optik 126(23), 4149–4154 (2015).
[Crossref]

2014 (4)

Z. Wei, M. Shao, G. Zhang, and Y. Wang, “Parallel-based calibration method for line-structured light vision sensor,” Opt. Eng. 53(3), 033101 (2014).
[Crossref]

Z. Wei, C. Li, and B. Ding, “Line structured light vision sensor calibration using parallel straight lines features,” Optik - Int. J. for Light. Electron Opt. 125(17), 4990–4997 (2014).
[Crossref]

L. Zhen, L. Fengjiao, H. Bangkui, and Z. Guangjun, “Real-time and accurate rail wear measurement method and experimental analysis,” J. Opt. Soc. Am. A 31(8), 1721–1730 (2014).
[Crossref]

Z. Xie, X. Wang, and S. Chi, “Simultaneous calibration of the intrinsic and extrinsic parameters of structured-light sensors,” Opt. Lasers Eng. 58, 9–18 (2014).
[Crossref]

2013 (4)

A. Ben-Hamadou, C. Soussen, C. Daul, W. Blondel, and D. Wolf, “Flexible calibration of structured-light systems projecting point patterns,” Comput. Vis. & Image Underst. 117(10), 1468–1481 (2013).
[Crossref]

J. E. Ha and K. W. Her, “Calibration of structured light stripe system using plane with slits,” Opt. Eng. 52(1), 013602 (2013).
[Crossref]

Y. G. Huang, X. H. Li, and P. F. Chen, “Calibration method for line-structured light multi-vision sensor based on combined target,” Eurasip J. on Wirel. Commun. Netw. 2013(1), 92 (2013).
[Crossref]

Y. Xianghua, P. Kun, H. Yongbo, G. Sheng, K. Jing, and Z. Hongbin, “Self-calibration of catadioptric camera with two planar mirrors from silhouettes,” IEEE Transactions on Pattern Analysis Mach. Intell. 35(5), 1206–1220 (2013).
[Crossref]

2011 (2)

W. Kwan-Yee Kenneth, Z. Guoqiang, and C. Zhihu, “A stratified approach for camera calibration using spheres,” IEEE Trans. Image Process. 20(2), 305–316 (2011).
[Crossref]

H. Y. Xiong, X. You, and Z. J. Zong, “Accurate extrinsic calibration method of line structured-light sensor based on standard ball,” IET Image Process. 5(5), 369–375 (2011).
[Crossref]

2010 (2)

Z. Wei, L. Cao, and G. Zhang, “A novel 1d target-based calibration method with unknown orientation for structured light vision sensor,” Opt. Laser Technol. 42(4), 570–574 (2010).
[Crossref]

G. Zhang, L. Zhen, J. Sun, and Z. Wei, “Novel calibration method for a multi-sensor visual measurement system based on structured light,” Opt. Eng. 49(4), 043602 (2010).
[Crossref]

2009 (2)

J. Sun, “Universal method for calibrating structured-light vision sensor on the spot,” J. Mech. Eng. 45(03), 174–177 (2009).
[Crossref]

D. Lanman, D. Crispell, and G. Taubin, “Surround structured lighting: 3-D scanning with orthographic illumination,” Comp. Vision Image Underst. 113, 1107–1117 (2009).
[Crossref]

2008 (2)

2007 (1)

Z. Hui, K. Wong, and Z. Guoqiang, “Camera calibration from images of spheres,” IEEE Transactions on Pattern Analysis Mach. Intell. 29(3), 499–502 (2007).
[Crossref]

2005 (2)

F. Zhou and G. Zhang, “Complete calibration of a structured light stripe vision sensor through planar target of unknown orientations,” Image Vis. Comput. 23(1), 59–67 (2005).
[Crossref]

A. Y. Yang, K. Huang, S. Rao, H. Wei, and M. Yi, “Symmetry-based 3-d reconstruction from perspective images,” Comput. Vis. Image Underst. 99(2), 210–240 (2005).
[Crossref]

2004 (2)

K. H. Jang, H. L. Dong, and S. K. Jung, “A moving planar mirror based approach for cultural reconstruction,” Comput. Animat. Virtual Worlds 15(34), 415–423 (2004).
[Crossref]

Z. Zhang, “Camera calibration with one-dimensional objects,” IEEE Transactions on Pattern Analysis Mach. Intell. 26(7), 892–899 (2004).
[Crossref]

2003 (1)

A. R. J. Francois, G. G. Medioni, and R. Waupotitsch, “Mirror symmetry: 2-view stereo geometry,” Image Vis. Comput. 21(2), 137–143 (2003).
[Crossref]

2001 (1)

J. Gluckman and S. K. Nayar, “Catadioptric stereo system using planar mirrors,” Intnl. J. Computer Vision 44, 65–79 (2001).
[Crossref]

2000 (1)

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

1999 (1)

D. Q. Huynh, R. A. Owens, and P. E. Hartmann, “Calibrating a structured light stripe system: A novel approach,” Int. J. Comput. Vis. 33(1), 73–86 (1999).
[Crossref]

1998 (1)

C. Steger, “An unbiased detector of curvilinear structures,” IEEE Trans. Pattern Anal. Machine Intell. 20(2), 113–125 (1998).
[Crossref]

Ait-Aider, O.

P. Lébraly, C. Deymier, O. Ait-Aider, E. Royer, and M. Dhome, “Flexible extrinsic calibration of non-overlapping cameras using a planar mirror: Application to vision-based robotics,” in IEEE/RSJ International Conference on Intelligent Robots and Systems, (2010).

Al-Hamadi, A.

E. Lilienblum and A. Al-Hamadi, “A structured light approach for 3d surface reconstruction with a stereo line-scan system,” in Instrumentation Measurement Technology Conference, (2015).

Arnspang, J.

B. K. Ramsgaard, I. Balslev, and J. Arnspang, “Mirror-based trinocular systems in robot-vision,” in International Conference on Pattern Recognition, (2000).

Balslev, I.

B. K. Ramsgaard, I. Balslev, and J. Arnspang, “Mirror-based trinocular systems in robot-vision,” in International Conference on Pattern Recognition, (2000).

Bangkui, H.

Barreto, J. P.

R. Rui, J. P. Barreto, and U. Nunes, “Camera pose estimation using images of plane mirror reflections,” in European Conference on Computer Vision, (2010).

Ben-Hamadou, A.

A. Ben-Hamadou, C. Soussen, C. Daul, W. Blondel, and D. Wolf, “Flexible calibration of structured-light systems projecting point patterns,” Comput. Vis. & Image Underst. 117(10), 1468–1481 (2013).
[Crossref]

Blondel, W.

A. Ben-Hamadou, C. Soussen, C. Daul, W. Blondel, and D. Wolf, “Flexible calibration of structured-light systems projecting point patterns,” Comput. Vis. & Image Underst. 117(10), 1468–1481 (2013).
[Crossref]

Bouguet, J. Y.

J. Y. Bouguet, “The MATLAB open source calibration toolbox,” http://www.vision.caltech.edu/bouguetj/calib_doc/index.html .

Cao, L.

Z. Wei, L. Cao, and G. Zhang, “A novel 1d target-based calibration method with unknown orientation for structured light vision sensor,” Opt. Laser Technol. 42(4), 570–574 (2010).
[Crossref]

Chen, P. F.

Y. G. Huang, X. H. Li, and P. F. Chen, “Calibration method for line-structured light multi-vision sensor based on combined target,” Eurasip J. on Wirel. Commun. Netw. 2013(1), 92 (2013).
[Crossref]

Chi, S.

Z. Xie, X. Wang, and S. Chi, “Simultaneous calibration of the intrinsic and extrinsic parameters of structured-light sensors,” Opt. Lasers Eng. 58, 9–18 (2014).
[Crossref]

Crispell, D.

D. Lanman, D. Crispell, and G. Taubin, “Surround structured lighting: 3-D scanning with orthographic illumination,” Comp. Vision Image Underst. 113, 1107–1117 (2009).
[Crossref]

Daul, C.

A. Ben-Hamadou, C. Soussen, C. Daul, W. Blondel, and D. Wolf, “Flexible calibration of structured-light systems projecting point patterns,” Comput. Vis. & Image Underst. 117(10), 1468–1481 (2013).
[Crossref]

Deymier, C.

P. Lébraly, C. Deymier, O. Ait-Aider, E. Royer, and M. Dhome, “Flexible extrinsic calibration of non-overlapping cameras using a planar mirror: Application to vision-based robotics,” in IEEE/RSJ International Conference on Intelligent Robots and Systems, (2010).

Dhome, M.

P. Lébraly, C. Deymier, O. Ait-Aider, E. Royer, and M. Dhome, “Flexible extrinsic calibration of non-overlapping cameras using a planar mirror: Application to vision-based robotics,” in IEEE/RSJ International Conference on Intelligent Robots and Systems, (2010).

Ding, B.

Z. Wei, C. Li, and B. Ding, “Line structured light vision sensor calibration using parallel straight lines features,” Optik - Int. J. for Light. Electron Opt. 125(17), 4990–4997 (2014).
[Crossref]

Dong, H. L.

K. H. Jang, H. L. Dong, and S. K. Jung, “A moving planar mirror based approach for cultural reconstruction,” Comput. Animat. Virtual Worlds 15(34), 415–423 (2004).
[Crossref]

Fengjiao, L.

Frahm, J. M.

R. K. Kumar, A. Ilie, J. M. Frahm, and M. Pollefeys, “Simple calibration of non-overlapping cameras with a mirror,” in Proc IEEE Conference on Computer Vision and Pattern Recognition, (2008).

Francois, A. R. J.

A. R. J. Francois, G. G. Medioni, and R. Waupotitsch, “Mirror symmetry: 2-view stereo geometry,” Image Vis. Comput. 21(2), 137–143 (2003).
[Crossref]

Gluckman, J.

J. Gluckman and S. K. Nayar, “Catadioptric stereo system using planar mirrors,” Intnl. J. Computer Vision 44, 65–79 (2001).
[Crossref]

Gong, Z.

Guangjun, Z.

Guoqiang, Z.

W. Kwan-Yee Kenneth, Z. Guoqiang, and C. Zhihu, “A stratified approach for camera calibration using spheres,” IEEE Trans. Image Process. 20(2), 305–316 (2011).
[Crossref]

Z. Hui, K. Wong, and Z. Guoqiang, “Camera calibration from images of spheres,” IEEE Transactions on Pattern Analysis Mach. Intell. 29(3), 499–502 (2007).
[Crossref]

Ha, J. E.

J. E. Ha and K. W. Her, “Calibration of structured light stripe system using plane with slits,” Opt. Eng. 52(1), 013602 (2013).
[Crossref]

Hartley, R.

R. Hartley and A. Zisserman, “Multiple view geometry in computer vision,” Kybernetes 30, 1865–1872 (2008).

M. Liu, R. Hartley, and M. Salzmann, “Mirror surface reconstruction from a single image,” in Proc IEEE Conference on Computer Vision and Pattern Recognition, (2013).

Hartmann, P. E.

D. Q. Huynh, R. A. Owens, and P. E. Hartmann, “Calibrating a structured light stripe system: A novel approach,” Int. J. Comput. Vis. 33(1), 73–86 (1999).
[Crossref]

Hayashi, N.

N. Hayashi, T. Tomizawa, T. Suehiro, and S. Kudoh, “Stereo calibration method using mirrored images containing a camera,” in IEEE International Conference on Robotics and Biomimetics, (2014).

Her, K. W.

J. E. Ha and K. W. Her, “Calibration of structured light stripe system using plane with slits,” Opt. Eng. 52(1), 013602 (2013).
[Crossref]

Hesch, J. A.

J. A. Hesch, A. I. Mourikis, and S. I. Roumelioti, “Extrinsic camera calibration using mulitiple reflections,” in European Conference on Computer Vision, (2010).

Hongbin, Z.

Y. Xianghua, P. Kun, H. Yongbo, G. Sheng, K. Jing, and Z. Hongbin, “Self-calibration of catadioptric camera with two planar mirrors from silhouettes,” IEEE Transactions on Pattern Analysis Mach. Intell. 35(5), 1206–1220 (2013).
[Crossref]

Huang, K.

A. Y. Yang, K. Huang, S. Rao, H. Wei, and M. Yi, “Symmetry-based 3-d reconstruction from perspective images,” Comput. Vis. Image Underst. 99(2), 210–240 (2005).
[Crossref]

Huang, Y. G.

Y. G. Huang, X. H. Li, and P. F. Chen, “Calibration method for line-structured light multi-vision sensor based on combined target,” Eurasip J. on Wirel. Commun. Netw. 2013(1), 92 (2013).
[Crossref]

Hui, Z.

Z. Hui, K. Wong, and Z. Guoqiang, “Camera calibration from images of spheres,” IEEE Transactions on Pattern Analysis Mach. Intell. 29(3), 499–502 (2007).
[Crossref]

Huynh, D. Q.

D. Q. Huynh, R. A. Owens, and P. E. Hartmann, “Calibrating a structured light stripe system: A novel approach,” Int. J. Comput. Vis. 33(1), 73–86 (1999).
[Crossref]

Ilie, A.

R. K. Kumar, A. Ilie, J. M. Frahm, and M. Pollefeys, “Simple calibration of non-overlapping cameras with a mirror,” in Proc IEEE Conference on Computer Vision and Pattern Recognition, (2008).

Jang, K. H.

K. H. Jang, H. L. Dong, and S. K. Jung, “A moving planar mirror based approach for cultural reconstruction,” Comput. Animat. Virtual Worlds 15(34), 415–423 (2004).
[Crossref]

Jing, K.

Y. Xianghua, P. Kun, H. Yongbo, G. Sheng, K. Jing, and Z. Hongbin, “Self-calibration of catadioptric camera with two planar mirrors from silhouettes,” IEEE Transactions on Pattern Analysis Mach. Intell. 35(5), 1206–1220 (2013).
[Crossref]

Jung, S. K.

K. H. Jang, H. L. Dong, and S. K. Jung, “A moving planar mirror based approach for cultural reconstruction,” Comput. Animat. Virtual Worlds 15(34), 415–423 (2004).
[Crossref]

Kudoh, S.

N. Hayashi, T. Tomizawa, T. Suehiro, and S. Kudoh, “Stereo calibration method using mirrored images containing a camera,” in IEEE International Conference on Robotics and Biomimetics, (2014).

Kumar, R. K.

R. K. Kumar, A. Ilie, J. M. Frahm, and M. Pollefeys, “Simple calibration of non-overlapping cameras with a mirror,” in Proc IEEE Conference on Computer Vision and Pattern Recognition, (2008).

Kun, P.

Y. Xianghua, P. Kun, H. Yongbo, G. Sheng, K. Jing, and Z. Hongbin, “Self-calibration of catadioptric camera with two planar mirrors from silhouettes,” IEEE Transactions on Pattern Analysis Mach. Intell. 35(5), 1206–1220 (2013).
[Crossref]

Kutulakos, K. N.

M. O’Toole, J. Mather, and K. N. Kutulakos, “3d shape and indirect appearance by structured light transport,” in Computer Vision Pattern Recognition, (2014).

Kwan-Yee Kenneth, W.

W. Kwan-Yee Kenneth, Z. Guoqiang, and C. Zhihu, “A stratified approach for camera calibration using spheres,” IEEE Trans. Image Process. 20(2), 305–316 (2011).
[Crossref]

Lanman, D.

D. Lanman, D. Crispell, and G. Taubin, “Surround structured lighting: 3-D scanning with orthographic illumination,” Comp. Vision Image Underst. 113, 1107–1117 (2009).
[Crossref]

Lébraly, P.

P. Lébraly, C. Deymier, O. Ait-Aider, E. Royer, and M. Dhome, “Flexible extrinsic calibration of non-overlapping cameras using a planar mirror: Application to vision-based robotics,” in IEEE/RSJ International Conference on Intelligent Robots and Systems, (2010).

Li, C.

Z. Wei, C. Li, and B. Ding, “Line structured light vision sensor calibration using parallel straight lines features,” Optik - Int. J. for Light. Electron Opt. 125(17), 4990–4997 (2014).
[Crossref]

Li, F.

L. Zhen, X. Li, F. Li, and G. Zhang, “Calibration method for line-structured light vision sensor based on a single ball target,” Opt. Lasers Eng. 69, 20–28 (2015).
[Crossref]

Li, X.

L. Zhen, X. Li, F. Li, and G. Zhang, “Calibration method for line-structured light vision sensor based on a single ball target,” Opt. Lasers Eng. 69, 20–28 (2015).
[Crossref]

Z. Liu, X. Li, and Y. Yin, “On-site calibration of line-structured light vision sensor in complex light environments,” Opt. Express 23(23), 29896–29911 (2015).
[Crossref]

Li, X. H.

Y. G. Huang, X. H. Li, and P. F. Chen, “Calibration method for line-structured light multi-vision sensor based on combined target,” Eurasip J. on Wirel. Commun. Netw. 2013(1), 92 (2013).
[Crossref]

Lilienblum, E.

E. Lilienblum and A. Al-Hamadi, “A structured light approach for 3d surface reconstruction with a stereo line-scan system,” in Instrumentation Measurement Technology Conference, (2015).

Liu, M.

M. Liu, R. Hartley, and M. Salzmann, “Mirror surface reconstruction from a single image,” in Proc IEEE Conference on Computer Vision and Pattern Recognition, (2013).

Liu, S.

S. Liu, Q. Tan, and Y. Zhang, “Shaft diameter measurement using structured light vision,” Sensors 15(8), 19750–19767 (2015).
[Crossref]

Liu, Z.

Mather, J.

M. O’Toole, J. Mather, and K. N. Kutulakos, “3d shape and indirect appearance by structured light transport,” in Computer Vision Pattern Recognition, (2014).

Matsuyama, T.

K. Takahashi, S. Nobuhara, and T. Matsuyama, “A new mirror-based extrinsic camera calibration using an orthogonality constraint,” in IEEE Conference on Computer Vision and Pattern Recognition, (2012).

Medioni, G. G.

A. R. J. Francois, G. G. Medioni, and R. Waupotitsch, “Mirror symmetry: 2-view stereo geometry,” Image Vis. Comput. 21(2), 137–143 (2003).
[Crossref]

Mourikis, A. I.

J. A. Hesch, A. I. Mourikis, and S. I. Roumelioti, “Extrinsic camera calibration using mulitiple reflections,” in European Conference on Computer Vision, (2010).

Nayar, S. K.

J. Gluckman and S. K. Nayar, “Catadioptric stereo system using planar mirrors,” Intnl. J. Computer Vision 44, 65–79 (2001).
[Crossref]

Nobuhara, S.

K. Takahashi, S. Nobuhara, and T. Matsuyama, “A new mirror-based extrinsic camera calibration using an orthogonality constraint,” in IEEE Conference on Computer Vision and Pattern Recognition, (2012).

Nunes, U.

R. Rui, J. P. Barreto, and U. Nunes, “Camera pose estimation using images of plane mirror reflections,” in European Conference on Computer Vision, (2010).

O’Toole, M.

M. O’Toole, J. Mather, and K. N. Kutulakos, “3d shape and indirect appearance by structured light transport,” in Computer Vision Pattern Recognition, (2014).

Owens, R. A.

D. Q. Huynh, R. A. Owens, and P. E. Hartmann, “Calibrating a structured light stripe system: A novel approach,” Int. J. Comput. Vis. 33(1), 73–86 (1999).
[Crossref]

Pollefeys, M.

R. K. Kumar, A. Ilie, J. M. Frahm, and M. Pollefeys, “Simple calibration of non-overlapping cameras with a mirror,” in Proc IEEE Conference on Computer Vision and Pattern Recognition, (2008).

Ramsgaard, B. K.

B. K. Ramsgaard, I. Balslev, and J. Arnspang, “Mirror-based trinocular systems in robot-vision,” in International Conference on Pattern Recognition, (2000).

Rao, S.

A. Y. Yang, K. Huang, S. Rao, H. Wei, and M. Yi, “Symmetry-based 3-d reconstruction from perspective images,” Comput. Vis. Image Underst. 99(2), 210–240 (2005).
[Crossref]

Roumelioti, S. I.

J. A. Hesch, A. I. Mourikis, and S. I. Roumelioti, “Extrinsic camera calibration using mulitiple reflections,” in European Conference on Computer Vision, (2010).

Royer, E.

P. Lébraly, C. Deymier, O. Ait-Aider, E. Royer, and M. Dhome, “Flexible extrinsic calibration of non-overlapping cameras using a planar mirror: Application to vision-based robotics,” in IEEE/RSJ International Conference on Intelligent Robots and Systems, (2010).

Rui, R.

R. Rui, J. P. Barreto, and U. Nunes, “Camera pose estimation using images of plane mirror reflections,” in European Conference on Computer Vision, (2010).

Salzmann, M.

M. Liu, R. Hartley, and M. Salzmann, “Mirror surface reconstruction from a single image,” in Proc IEEE Conference on Computer Vision and Pattern Recognition, (2013).

Shao, M.

Z. Wei, M. Shao, G. Zhang, and Y. Wang, “Parallel-based calibration method for line-structured light vision sensor,” Opt. Eng. 53(3), 033101 (2014).
[Crossref]

Sheng, G.

Y. Xianghua, P. Kun, H. Yongbo, G. Sheng, K. Jing, and Z. Hongbin, “Self-calibration of catadioptric camera with two planar mirrors from silhouettes,” IEEE Transactions on Pattern Analysis Mach. Intell. 35(5), 1206–1220 (2013).
[Crossref]

Shing-Tung, Y.

Song, Z.

Soussen, C.

A. Ben-Hamadou, C. Soussen, C. Daul, W. Blondel, and D. Wolf, “Flexible calibration of structured-light systems projecting point patterns,” Comput. Vis. & Image Underst. 117(10), 1468–1481 (2013).
[Crossref]

Steger, C.

C. Steger, “An unbiased detector of curvilinear structures,” IEEE Trans. Pattern Anal. Machine Intell. 20(2), 113–125 (1998).
[Crossref]

Suehiro, T.

N. Hayashi, T. Tomizawa, T. Suehiro, and S. Kudoh, “Stereo calibration method using mirrored images containing a camera,” in IEEE International Conference on Robotics and Biomimetics, (2014).

Sun, J.

Z. Gong, J. Sun, and G. Zhang, “Dynamic structured-light measurement for wheel diameter based on the cycloid constraint,” Appl. Opt. 55(1), 198–207 (2016).
[Crossref]

G. Zhang, L. Zhen, J. Sun, and Z. Wei, “Novel calibration method for a multi-sensor visual measurement system based on structured light,” Opt. Eng. 49(4), 043602 (2010).
[Crossref]

J. Sun, “Universal method for calibrating structured-light vision sensor on the spot,” J. Mech. Eng. 45(03), 174–177 (2009).
[Crossref]

Takahashi, K.

K. Takahashi, S. Nobuhara, and T. Matsuyama, “A new mirror-based extrinsic camera calibration using an orthogonality constraint,” in IEEE Conference on Computer Vision and Pattern Recognition, (2012).

Tan, Q.

S. Liu, Q. Tan, and Y. Zhang, “Shaft diameter measurement using structured light vision,” Sensors 15(8), 19750–19767 (2015).
[Crossref]

Taubin, G.

D. Lanman, D. Crispell, and G. Taubin, “Surround structured lighting: 3-D scanning with orthographic illumination,” Comp. Vision Image Underst. 113, 1107–1117 (2009).
[Crossref]

Tomizawa, T.

N. Hayashi, T. Tomizawa, T. Suehiro, and S. Kudoh, “Stereo calibration method using mirrored images containing a camera,” in IEEE International Conference on Robotics and Biomimetics, (2014).

Tsui, H. T.

Z. Y. Zhang and H. T. Tsui, “3d reconstruction from a single view of an object and its image in a plane mirror,” in International Conference on Pattern Recognition, (1998).

Wang, X.

Z. Xie, X. Wang, and S. Chi, “Simultaneous calibration of the intrinsic and extrinsic parameters of structured-light sensors,” Opt. Lasers Eng. 58, 9–18 (2014).
[Crossref]

Wang, Y.

Z. Xu, Y. Wang, and C. Yang, “Multi-camera global calibration for large-scale measurement based on plane mirror,” Optik 126(23), 4149–4154 (2015).
[Crossref]

Z. Wei, M. Shao, G. Zhang, and Y. Wang, “Parallel-based calibration method for line-structured light vision sensor,” Opt. Eng. 53(3), 033101 (2014).
[Crossref]

Waupotitsch, R.

A. R. J. Francois, G. G. Medioni, and R. Waupotitsch, “Mirror symmetry: 2-view stereo geometry,” Image Vis. Comput. 21(2), 137–143 (2003).
[Crossref]

Wei, H.

A. Y. Yang, K. Huang, S. Rao, H. Wei, and M. Yi, “Symmetry-based 3-d reconstruction from perspective images,” Comput. Vis. Image Underst. 99(2), 210–240 (2005).
[Crossref]

Wei, Z.

Z. Wei, C. Li, and B. Ding, “Line structured light vision sensor calibration using parallel straight lines features,” Optik - Int. J. for Light. Electron Opt. 125(17), 4990–4997 (2014).
[Crossref]

Z. Wei, M. Shao, G. Zhang, and Y. Wang, “Parallel-based calibration method for line-structured light vision sensor,” Opt. Eng. 53(3), 033101 (2014).
[Crossref]

Z. Wei, L. Cao, and G. Zhang, “A novel 1d target-based calibration method with unknown orientation for structured light vision sensor,” Opt. Laser Technol. 42(4), 570–574 (2010).
[Crossref]

G. Zhang, L. Zhen, J. Sun, and Z. Wei, “Novel calibration method for a multi-sensor visual measurement system based on structured light,” Opt. Eng. 49(4), 043602 (2010).
[Crossref]

Wolf, D.

A. Ben-Hamadou, C. Soussen, C. Daul, W. Blondel, and D. Wolf, “Flexible calibration of structured-light systems projecting point patterns,” Comput. Vis. & Image Underst. 117(10), 1468–1481 (2013).
[Crossref]

Wong, K.

Z. Hui, K. Wong, and Z. Guoqiang, “Camera calibration from images of spheres,” IEEE Transactions on Pattern Analysis Mach. Intell. 29(3), 499–502 (2007).
[Crossref]

Xianghua, Y.

Y. Xianghua, P. Kun, H. Yongbo, G. Sheng, K. Jing, and Z. Hongbin, “Self-calibration of catadioptric camera with two planar mirrors from silhouettes,” IEEE Transactions on Pattern Analysis Mach. Intell. 35(5), 1206–1220 (2013).
[Crossref]

Xie, Z.

Z. Xie, X. Wang, and S. Chi, “Simultaneous calibration of the intrinsic and extrinsic parameters of structured-light sensors,” Opt. Lasers Eng. 58, 9–18 (2014).
[Crossref]

Xiong, H. Y.

H. Y. Xiong, X. You, and Z. J. Zong, “Accurate extrinsic calibration method of line structured-light sensor based on standard ball,” IET Image Process. 5(5), 369–375 (2011).
[Crossref]

Xu, Z.

Z. Xu, Y. Wang, and C. Yang, “Multi-camera global calibration for large-scale measurement based on plane mirror,” Optik 126(23), 4149–4154 (2015).
[Crossref]

Yang, A. Y.

A. Y. Yang, K. Huang, S. Rao, H. Wei, and M. Yi, “Symmetry-based 3-d reconstruction from perspective images,” Comput. Vis. Image Underst. 99(2), 210–240 (2005).
[Crossref]

Yang, C.

Z. Xu, Y. Wang, and C. Yang, “Multi-camera global calibration for large-scale measurement based on plane mirror,” Optik 126(23), 4149–4154 (2015).
[Crossref]

Yi, M.

A. Y. Yang, K. Huang, S. Rao, H. Wei, and M. Yi, “Symmetry-based 3-d reconstruction from perspective images,” Comput. Vis. Image Underst. 99(2), 210–240 (2005).
[Crossref]

Yin, Y.

Yongbo, H.

Y. Xianghua, P. Kun, H. Yongbo, G. Sheng, K. Jing, and Z. Hongbin, “Self-calibration of catadioptric camera with two planar mirrors from silhouettes,” IEEE Transactions on Pattern Analysis Mach. Intell. 35(5), 1206–1220 (2013).
[Crossref]

You, X.

H. Y. Xiong, X. You, and Z. J. Zong, “Accurate extrinsic calibration method of line structured-light sensor based on standard ball,” IET Image Process. 5(5), 369–375 (2011).
[Crossref]

Zhang, G.

Z. Gong, J. Sun, and G. Zhang, “Dynamic structured-light measurement for wheel diameter based on the cycloid constraint,” Appl. Opt. 55(1), 198–207 (2016).
[Crossref]

L. Zhen, X. Li, F. Li, and G. Zhang, “Calibration method for line-structured light vision sensor based on a single ball target,” Opt. Lasers Eng. 69, 20–28 (2015).
[Crossref]

Z. Wei, M. Shao, G. Zhang, and Y. Wang, “Parallel-based calibration method for line-structured light vision sensor,” Opt. Eng. 53(3), 033101 (2014).
[Crossref]

Z. Wei, L. Cao, and G. Zhang, “A novel 1d target-based calibration method with unknown orientation for structured light vision sensor,” Opt. Laser Technol. 42(4), 570–574 (2010).
[Crossref]

G. Zhang, L. Zhen, J. Sun, and Z. Wei, “Novel calibration method for a multi-sensor visual measurement system based on structured light,” Opt. Eng. 49(4), 043602 (2010).
[Crossref]

F. Zhou and G. Zhang, “Complete calibration of a structured light stripe vision sensor through planar target of unknown orientations,” Image Vis. Comput. 23(1), 59–67 (2005).
[Crossref]

Zhang, Y.

S. Liu, Q. Tan, and Y. Zhang, “Shaft diameter measurement using structured light vision,” Sensors 15(8), 19750–19767 (2015).
[Crossref]

Zhang, Z.

Z. Zhang, “Camera calibration with one-dimensional objects,” IEEE Transactions on Pattern Analysis Mach. Intell. 26(7), 892–899 (2004).
[Crossref]

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

Zhang, Z. Y.

Z. Y. Zhang and H. T. Tsui, “3d reconstruction from a single view of an object and its image in a plane mirror,” in International Conference on Pattern Recognition, (1998).

Zhen, L.

L. Zhen, X. Li, F. Li, and G. Zhang, “Calibration method for line-structured light vision sensor based on a single ball target,” Opt. Lasers Eng. 69, 20–28 (2015).
[Crossref]

L. Zhen, L. Fengjiao, H. Bangkui, and Z. Guangjun, “Real-time and accurate rail wear measurement method and experimental analysis,” J. Opt. Soc. Am. A 31(8), 1721–1730 (2014).
[Crossref]

G. Zhang, L. Zhen, J. Sun, and Z. Wei, “Novel calibration method for a multi-sensor visual measurement system based on structured light,” Opt. Eng. 49(4), 043602 (2010).
[Crossref]

Zhihu, C.

W. Kwan-Yee Kenneth, Z. Guoqiang, and C. Zhihu, “A stratified approach for camera calibration using spheres,” IEEE Trans. Image Process. 20(2), 305–316 (2011).
[Crossref]

Zhou, F.

F. Zhou and G. Zhang, “Complete calibration of a structured light stripe vision sensor through planar target of unknown orientations,” Image Vis. Comput. 23(1), 59–67 (2005).
[Crossref]

Zisserman, A.

R. Hartley and A. Zisserman, “Multiple view geometry in computer vision,” Kybernetes 30, 1865–1872 (2008).

Zong, Z. J.

H. Y. Xiong, X. You, and Z. J. Zong, “Accurate extrinsic calibration method of line structured-light sensor based on standard ball,” IET Image Process. 5(5), 369–375 (2011).
[Crossref]

Appl. Opt. (2)

Comp. Vision Image Underst. (1)

D. Lanman, D. Crispell, and G. Taubin, “Surround structured lighting: 3-D scanning with orthographic illumination,” Comp. Vision Image Underst. 113, 1107–1117 (2009).
[Crossref]

Comput. Animat. Virtual Worlds (1)

K. H. Jang, H. L. Dong, and S. K. Jung, “A moving planar mirror based approach for cultural reconstruction,” Comput. Animat. Virtual Worlds 15(34), 415–423 (2004).
[Crossref]

Comput. Vis. & Image Underst. (1)

A. Ben-Hamadou, C. Soussen, C. Daul, W. Blondel, and D. Wolf, “Flexible calibration of structured-light systems projecting point patterns,” Comput. Vis. & Image Underst. 117(10), 1468–1481 (2013).
[Crossref]

Comput. Vis. Image Underst. (1)

A. Y. Yang, K. Huang, S. Rao, H. Wei, and M. Yi, “Symmetry-based 3-d reconstruction from perspective images,” Comput. Vis. Image Underst. 99(2), 210–240 (2005).
[Crossref]

Eurasip J. on Wirel. Commun. Netw. (1)

Y. G. Huang, X. H. Li, and P. F. Chen, “Calibration method for line-structured light multi-vision sensor based on combined target,” Eurasip J. on Wirel. Commun. Netw. 2013(1), 92 (2013).
[Crossref]

IEEE Trans. Image Process. (1)

W. Kwan-Yee Kenneth, Z. Guoqiang, and C. Zhihu, “A stratified approach for camera calibration using spheres,” IEEE Trans. Image Process. 20(2), 305–316 (2011).
[Crossref]

IEEE Trans. Pattern Anal. Machine Intell. (2)

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

C. Steger, “An unbiased detector of curvilinear structures,” IEEE Trans. Pattern Anal. Machine Intell. 20(2), 113–125 (1998).
[Crossref]

IEEE Transactions on Pattern Analysis Mach. Intell. (3)

Z. Hui, K. Wong, and Z. Guoqiang, “Camera calibration from images of spheres,” IEEE Transactions on Pattern Analysis Mach. Intell. 29(3), 499–502 (2007).
[Crossref]

Y. Xianghua, P. Kun, H. Yongbo, G. Sheng, K. Jing, and Z. Hongbin, “Self-calibration of catadioptric camera with two planar mirrors from silhouettes,” IEEE Transactions on Pattern Analysis Mach. Intell. 35(5), 1206–1220 (2013).
[Crossref]

Z. Zhang, “Camera calibration with one-dimensional objects,” IEEE Transactions on Pattern Analysis Mach. Intell. 26(7), 892–899 (2004).
[Crossref]

IET Image Process. (1)

H. Y. Xiong, X. You, and Z. J. Zong, “Accurate extrinsic calibration method of line structured-light sensor based on standard ball,” IET Image Process. 5(5), 369–375 (2011).
[Crossref]

Image Vis. Comput. (2)

F. Zhou and G. Zhang, “Complete calibration of a structured light stripe vision sensor through planar target of unknown orientations,” Image Vis. Comput. 23(1), 59–67 (2005).
[Crossref]

A. R. J. Francois, G. G. Medioni, and R. Waupotitsch, “Mirror symmetry: 2-view stereo geometry,” Image Vis. Comput. 21(2), 137–143 (2003).
[Crossref]

Int. J. Comput. Vis. (1)

D. Q. Huynh, R. A. Owens, and P. E. Hartmann, “Calibrating a structured light stripe system: A novel approach,” Int. J. Comput. Vis. 33(1), 73–86 (1999).
[Crossref]

Intnl. J. Computer Vision (1)

J. Gluckman and S. K. Nayar, “Catadioptric stereo system using planar mirrors,” Intnl. J. Computer Vision 44, 65–79 (2001).
[Crossref]

J. Mech. Eng. (1)

J. Sun, “Universal method for calibrating structured-light vision sensor on the spot,” J. Mech. Eng. 45(03), 174–177 (2009).
[Crossref]

J. Opt. Soc. Am. A (1)

Kybernetes (1)

R. Hartley and A. Zisserman, “Multiple view geometry in computer vision,” Kybernetes 30, 1865–1872 (2008).

Opt. Eng. (3)

Z. Wei, M. Shao, G. Zhang, and Y. Wang, “Parallel-based calibration method for line-structured light vision sensor,” Opt. Eng. 53(3), 033101 (2014).
[Crossref]

G. Zhang, L. Zhen, J. Sun, and Z. Wei, “Novel calibration method for a multi-sensor visual measurement system based on structured light,” Opt. Eng. 49(4), 043602 (2010).
[Crossref]

J. E. Ha and K. W. Her, “Calibration of structured light stripe system using plane with slits,” Opt. Eng. 52(1), 013602 (2013).
[Crossref]

Opt. Express (1)

Opt. Laser Technol. (1)

Z. Wei, L. Cao, and G. Zhang, “A novel 1d target-based calibration method with unknown orientation for structured light vision sensor,” Opt. Laser Technol. 42(4), 570–574 (2010).
[Crossref]

Opt. Lasers Eng. (2)

Z. Xie, X. Wang, and S. Chi, “Simultaneous calibration of the intrinsic and extrinsic parameters of structured-light sensors,” Opt. Lasers Eng. 58, 9–18 (2014).
[Crossref]

L. Zhen, X. Li, F. Li, and G. Zhang, “Calibration method for line-structured light vision sensor based on a single ball target,” Opt. Lasers Eng. 69, 20–28 (2015).
[Crossref]

Optik (1)

Z. Xu, Y. Wang, and C. Yang, “Multi-camera global calibration for large-scale measurement based on plane mirror,” Optik 126(23), 4149–4154 (2015).
[Crossref]

Optik - Int. J. for Light. Electron Opt. (1)

Z. Wei, C. Li, and B. Ding, “Line structured light vision sensor calibration using parallel straight lines features,” Optik - Int. J. for Light. Electron Opt. 125(17), 4990–4997 (2014).
[Crossref]

Sensors (1)

S. Liu, Q. Tan, and Y. Zhang, “Shaft diameter measurement using structured light vision,” Sensors 15(8), 19750–19767 (2015).
[Crossref]

Other (12)

Z. Y. Zhang and H. T. Tsui, “3d reconstruction from a single view of an object and its image in a plane mirror,” in International Conference on Pattern Recognition, (1998).

B. K. Ramsgaard, I. Balslev, and J. Arnspang, “Mirror-based trinocular systems in robot-vision,” in International Conference on Pattern Recognition, (2000).

J. A. Hesch, A. I. Mourikis, and S. I. Roumelioti, “Extrinsic camera calibration using mulitiple reflections,” in European Conference on Computer Vision, (2010).

R. Rui, J. P. Barreto, and U. Nunes, “Camera pose estimation using images of plane mirror reflections,” in European Conference on Computer Vision, (2010).

P. Lébraly, C. Deymier, O. Ait-Aider, E. Royer, and M. Dhome, “Flexible extrinsic calibration of non-overlapping cameras using a planar mirror: Application to vision-based robotics,” in IEEE/RSJ International Conference on Intelligent Robots and Systems, (2010).

K. Takahashi, S. Nobuhara, and T. Matsuyama, “A new mirror-based extrinsic camera calibration using an orthogonality constraint,” in IEEE Conference on Computer Vision and Pattern Recognition, (2012).

N. Hayashi, T. Tomizawa, T. Suehiro, and S. Kudoh, “Stereo calibration method using mirrored images containing a camera,” in IEEE International Conference on Robotics and Biomimetics, (2014).

R. K. Kumar, A. Ilie, J. M. Frahm, and M. Pollefeys, “Simple calibration of non-overlapping cameras with a mirror,” in Proc IEEE Conference on Computer Vision and Pattern Recognition, (2008).

M. O’Toole, J. Mather, and K. N. Kutulakos, “3d shape and indirect appearance by structured light transport,” in Computer Vision Pattern Recognition, (2014).

E. Lilienblum and A. Al-Hamadi, “A structured light approach for 3d surface reconstruction with a stereo line-scan system,” in Instrumentation Measurement Technology Conference, (2015).

M. Liu, R. Hartley, and M. Salzmann, “Mirror surface reconstruction from a single image,” in Proc IEEE Conference on Computer Vision and Pattern Recognition, (2013).

J. Y. Bouguet, “The MATLAB open source calibration toolbox,” http://www.vision.caltech.edu/bouguetj/calib_doc/index.html .

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Figures (17)

Fig. 1.
Fig. 1. Common targets for calibrating structured light vision sensors.
Fig. 2.
Fig. 2. Measurement principle of the structured light vision sensor. (a)Encoding structured light vision sensor. (b)Line-structured light vision sensor.
Fig. 3.
Fig. 3. The virtual binocular stereo vision measurement principle. The image of a real object in the real camera is equivalent to that the left camera in a binocular stereo vision system, whereas the image of real object in the mirror is equivalent to that the right camera in a binocular stereo vision system.
Fig. 4.
Fig. 4. The specific procedures of the proposed calibration method using the virtual binocular measuring principle.
Fig. 5.
Fig. 5. The coordinate transformation between the virtual and real cameras. The green arrow needs to transform the direction of ${X_V}$ to the right-hand coordinate frame.
Fig. 6.
Fig. 6. The solving of the virtual camera intrinsic parameters.
Fig. 7.
Fig. 7. Extraction of the light stripe center points.
Fig. 8.
Fig. 8. Matching of the light stripe center points. (a)Principle diagram of solving of the vanishing point. (b)Real image of solving of the vanishing point. (c)Matching of the light stripe center points.
Fig. 9.
Fig. 9. Auto-epipolar constraint in the image.
Fig. 10.
Fig. 10. Gray distribution of the light stripe on a metal surface, ceramic surface, and white paper. (a)Metal plane surface (expose time 2 ms). (b)Metal plane surface (expose time 9 ms). (c)White paper (expose time 2 ms). (d)Ceramic surface (expose time 2 ms).
Fig. 11.
Fig. 11. (a)The impact of extraction error of light stripe centers on the calibration accuracy. (b)The impact of the extraction error of the vanishing point on the calibration accuracy.
Fig. 12.
Fig. 12. The experiment platform. (a)Structured light sensor calibrated by the proposed method. (b)Structured light sensor calibrated by the LED plane target.
Fig. 13.
Fig. 13. Calibration images. (a)Images used for calibrating of intrinsic parameters of the real camera. (b)Five images of solving the vanishing point. (c)20 calibration images of left light stripe using the LED plane target. (d)20 calibration images of left light stripe using the plane mirror.
Fig. 14.
Fig. 14. (a)the yellow lines denote the matching lines solved by the vanishing points, that is, the connection line between the feature points on the real target and the vanishing points. (b)the yellow lines denote the matching lines, whereas the green lines denote the epipolar lines solved by the fundamental matrix.
Fig. 15.
Fig. 15. Comparison of calibration accuracy between the traditional evaluation method and the proposed evaluation method.
Fig. 16.
Fig. 16. (a)The physical picture of the standard step gauge block. (b)The obtained image of the standard step gauge block.
Fig. 17.
Fig. 17. The reconstruction of feature points based on invariance of the cross-ratio.

Tables (4)

Tables Icon

Table 1. Calibration results of the intrinsic parameters

Tables Icon

Table 2. Calibration results of the light plane

Tables Icon

Table 3. Measurement of the standard step gauge block (unit:mm)

Tables Icon

Table 4. Comparison of reconstruction accuracy of feature points (unit:mm)

Equations (26)

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

s [ u v 1 ] = K C [ I 3 × 3 , 0 3 × 1 ] [ X C Y C Z C 1 ] , K V = [ f x γ u 0 0 f y v 0 0 0 1 ] .
a X C + b Y C + c Z C + d = 0 ,
{ s 1 p ~ c = K C [ I 3 × 3 0 3 × 1 ] P ~ C s 2 p ~ v = K V [ R V C t V C ] P ~ C .
R C m = R ( φ m c ) R ( θ m c ) R ( δ m c ) = [ r 1 r 2 r 3 r 4 r 5 r 6 r 7 r 8 r 9 ] , t C m = [ t x t y t z ] .
[ X m m Y m m Z m m ] = [ cos 180 0 sin 180 0 1 0 sin 180 0 cos 180 ] [ X m Y m Z m ] = [ 1 0 0 0 1 0 0 0 1 ] [ X m m Y m m Z m m ] = R m m m [ X m m Y m m Z m m ] , t m m m = [ 0 0 0 ] .
φ m v = φ m c , θ m v = θ m c , δ m v = δ m c .
R V m m = [ r 1 r 2 r 3 r 4 r 5 r 6 r 7 r 8 r 9 ] , t V m m = [ t x t y t z ] .
R V m = R V m m R m m m , t V m = t V m m .
{ R V C = R V m R m C = R V m ( R V C ) 1 t V C = t V m R V m ( R C m ) 1 t C m .
{ u c = x c / x c d d x + u 0 v c = y c / d y + v 0 { u v = x c / x c d d x + u 0 v v = y c / d y + v 0
K V = [ f x γ u 0 0 f y v 0 0 0 1 ] ,
l C V i = m ~ C i × m ~ V i .
l v i = l C V i × l C V j ( i j ) .
f ( v ) = m i n i = 1 n ( ( l C V i ) T v ) 2 .
l e i = ( v v a n v C i v v a n u C i , 1 , u v a n v C i v v a n u C i v v a n u C i ) T .
F = K V T SR V C K C 1 ,
l e i = F p i .
l i = ( v v i + 1 v v i u v i + 1 u v i , 1 , u v i + 1 v v i v v i + 1 u v i u v i + 1 u v i ) T .
p i = [ l e i ] × l i ,
λ ( X T t i , Y T t i , 1 ) T = H h o r m 1 ( u t i , v t i , 1 ) .
( X C t i , Y C t i , Z C t i ) T = R C m ( X T t i , Y T t i , 0 ) + t C m ,
( X C m i , Y C m i , Z C m i ) T = ( P C i + s P V j ) / ( 1 + s ) ,
Δ d i = ( X m i X t i ) 2 + ( Y m i Y t i ) 2 + ( Z m i Z t i ) 2 .
K C = [ 3000 0 800 0 3000 600 0 0 1 ] .
0.8865 X + 0.1330 Y + 0.4432 Z 177.2969 = 0.
R C m = [ 0.6963  - 0.1131 0.7088 0.1234 0.9917 0.0371  - 0.7071 0.0617 0.7044 ] , t C m = [  - 10.00  - 100.00 500.00 ] .

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