Abstract

We propose a high-speed projection system that is able to project statistical speckle patterns at a rate of 500Hz. Its purpose is to generate structured light for a real-time photogrammetry stereo vision setup. As conventional digital light projector (DLP) projection setups are limited in their maximum projection rate to 250Hz for gray-value patterns, stripe projection systems are usually applied for real-time three-dimensional (3D) measurements. However, these techniques can only be used on steady surfaces as phase unwrapping has to be done. In contrast, the proposed setup is able to measure the shape of multiple spatially separated objects at once. We compare the speckle setup with a system using a DLP projector and with other fast 3D shape measurement setups, like the widely used stripe projection methods, qualitatively and quantitatively.

© 2010 Optical Society of America

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References

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  1. S. Zhang, “Recent progresses on real-time 3D shape measurement using digital fringe projection techniques,” Opt. Lasers Eng. 48, 149–158 (2010).
    [CrossRef]
  2. T. Weise, B. Leibe, and L. V. Gool, “Fast 3D scanning with automatic motion compensation,” in IEEE Conference on Computer Vision and Pattern Recognition (CVPR’07) (IEEE, 2007), pp. 1–8.
    [CrossRef]
  3. R. Yang, L. Wang, G. Welch, and M. Pollefeys, “Stereo vision on GPU,” in Workshop on Edge Computing Using New Commodity Architectures (University of North Carolina, 2006).
  4. S. Zhang, D. Royer, and S. Yau, “GPU-assisted high-resolution, real-time 3-D shape measurement,” Opt. Express 14, 9120–9129 (2006).
    [CrossRef] [PubMed]
  5. J. Pags, J. Salvi, R. Garcia, and C. Matabosch, “Overview of coded light projection techniques for automatic 3D profiling,” in IEEE Robotics and Automation (ICRA’03) (IEEE, 2003), Vol. 1, pp. 133–138.
  6. K. G. Harding, “Phase grating use for slop discrimination in moiré contouring,” Proc. SPIE 1614, 265–270 (1992).
    [CrossRef]
  7. Z. J. Geng, “Rainbow 3-D camera: new concept of high-speed three vision system,” Opt. Eng. 35, 376–383 (1996).
    [CrossRef]
  8. C. Wust and D. W. Capson, “Surface profile measurement using color fringe projection,” Machine Vis. Appl. 4, 193–203(1991).
    [CrossRef]
  9. L. Zhang, B. Curless, and S. M. Seitz, “Rapid shape acquisition using color structured light and multi-pass dynamic programming,” in IEEE Symposium on 3D Data Processing, Visualization, and Transmission (IEEE, 2002), pp. 24–36.
    [CrossRef]
  10. M. Takeda and K. Mutoh, “Fourier transform profilometry for the automatic measurement of 3-D object shapes,” Appl. Opt. 22, 3977–3982 (1983).
    [CrossRef] [PubMed]
  11. S. Rusinkiewicz, O. Hall-Holt, and M. Levoy, “Real-time 3D model acquisition,” in SIGGRAPH 2002 Proceedings (ACM, 2002), Vol. 21, pp. 438–446.
    [CrossRef]
  12. H. Guo and P. Huang, “3-D shape measurement by use of a modified Fourier transform method,” Proc. SPIE 7066, 70660E (2008).
    [CrossRef]
  13. B. Michaelis and P. Albrecht, “Stereo photogrammetry with improved spatial resolution,” in 14th International Conference on Pattern Recognition (IEEE, 1998), pp. 845–849.
  14. A. Wiegmann, H. Wagner, and R. Kowarschik, “Human face measurement by projecting bandlimited random patterns,” Opt. Express 14, 7692–7698 (2006).
    [CrossRef] [PubMed]
  15. J. P. Siebert and S. J. Marshall, “Human body 3D imaging by speckle texture projection photogrammetry,” Sensor Rev. 20, 218–226 (2000).
    [CrossRef]
  16. M. Dekiff, G. Bischoff, Z. Borocz, D. Dirksen, G. von Bally, and C. Denz, “3d-formerfassung mittels korrelation projizierter specklemuster,” in Deutsche Gesellschaft für angewandte Optik Proceedings (European Optical Society, 2008).
  17. M. Grosse and R. Kowarschik, “Space-time multiplexing in a stereo-photogrammetry setup,” in Fringe 2009, W.Osten and M.Kujawinska, eds. (Springer, 2009), pp. 755–759.
  18. J. P. Lewis, “Fast normalized-cross-correlation,” in Vision Interface (ACM, 1995).
  19. H. Hirschmller, P. R. Innocent, and J. Garibaldi, “Real-time correlation-based stereo vision with reduced border errors,” Int. J. Comput. Vis. 47, 229–246 (2002).
    [CrossRef]
  20. J. Davis, R. Ramamoorthi, and S. Rusinkiewicz, “Spacetime stereo: a unifying framework for depth from triangulation,” in IEEE Conference on Computer Vision and Pattern Recognition (CVPR’03) (IEEE, 2003), Vol. 2, pp. 359–366.
  21. J. Mairal, R. Keriven, and A. Chariot, “Fast and efficient dense variational stereo on GPU,” in Proceedings of International Symposium on 3D Data Processing, Visualization, and Transmission (IEEE, 2006), pp. 97–104.
  22. H. Wagner, A. Wiegmann, R. Kowarschik, and F. Zollner, “3D measurement of human face by stereophotogrammetry,” Proc. SPIE 5856, 509–516 (2005).
    [CrossRef]
  23. Z. Zhang, “A flexible new technique for camera calibration,” Tech. Rep. MSR-TR-98-71 (Microsoft Research, 1998).
  24. R. I. Hartley, “In defense of the 8-point algorithm,” IEEE Trans. Pattern Anal. Machine Intell. 19, 580–593 (1997).
    [CrossRef]
  25. J.C.Dainty, ed., Laser Speckle and Related Phenomena (Springer Verlag, 1984).
  26. M. Grosse, “Disturbing moiré effects in a stereo-photogrammetry setup,” in Deutsche Gesellschaft für angewandte Optik Proceedings (European Optical Society, 2009).
  27. S. Zhang, “High-resolution, real-time 3-D shape measurement,” Ph.D. dissertation (Stony Brook University, 2005).
  28. Centre Suisse d’Electronique et de Microtechnique, “Time of flight camera technology,” Tech. Rep. (Centre Suisse d’Electronique et de Microtechnique, 2009).

2010 (1)

S. Zhang, “Recent progresses on real-time 3D shape measurement using digital fringe projection techniques,” Opt. Lasers Eng. 48, 149–158 (2010).
[CrossRef]

2008 (1)

H. Guo and P. Huang, “3-D shape measurement by use of a modified Fourier transform method,” Proc. SPIE 7066, 70660E (2008).
[CrossRef]

2006 (2)

2005 (1)

H. Wagner, A. Wiegmann, R. Kowarschik, and F. Zollner, “3D measurement of human face by stereophotogrammetry,” Proc. SPIE 5856, 509–516 (2005).
[CrossRef]

2002 (1)

H. Hirschmller, P. R. Innocent, and J. Garibaldi, “Real-time correlation-based stereo vision with reduced border errors,” Int. J. Comput. Vis. 47, 229–246 (2002).
[CrossRef]

2000 (1)

J. P. Siebert and S. J. Marshall, “Human body 3D imaging by speckle texture projection photogrammetry,” Sensor Rev. 20, 218–226 (2000).
[CrossRef]

1997 (1)

R. I. Hartley, “In defense of the 8-point algorithm,” IEEE Trans. Pattern Anal. Machine Intell. 19, 580–593 (1997).
[CrossRef]

1996 (1)

Z. J. Geng, “Rainbow 3-D camera: new concept of high-speed three vision system,” Opt. Eng. 35, 376–383 (1996).
[CrossRef]

1992 (1)

K. G. Harding, “Phase grating use for slop discrimination in moiré contouring,” Proc. SPIE 1614, 265–270 (1992).
[CrossRef]

1991 (1)

C. Wust and D. W. Capson, “Surface profile measurement using color fringe projection,” Machine Vis. Appl. 4, 193–203(1991).
[CrossRef]

1983 (1)

Albrecht, P.

B. Michaelis and P. Albrecht, “Stereo photogrammetry with improved spatial resolution,” in 14th International Conference on Pattern Recognition (IEEE, 1998), pp. 845–849.

Bischoff, G.

M. Dekiff, G. Bischoff, Z. Borocz, D. Dirksen, G. von Bally, and C. Denz, “3d-formerfassung mittels korrelation projizierter specklemuster,” in Deutsche Gesellschaft für angewandte Optik Proceedings (European Optical Society, 2008).

Borocz, Z.

M. Dekiff, G. Bischoff, Z. Borocz, D. Dirksen, G. von Bally, and C. Denz, “3d-formerfassung mittels korrelation projizierter specklemuster,” in Deutsche Gesellschaft für angewandte Optik Proceedings (European Optical Society, 2008).

Capson, D. W.

C. Wust and D. W. Capson, “Surface profile measurement using color fringe projection,” Machine Vis. Appl. 4, 193–203(1991).
[CrossRef]

Chariot, A.

J. Mairal, R. Keriven, and A. Chariot, “Fast and efficient dense variational stereo on GPU,” in Proceedings of International Symposium on 3D Data Processing, Visualization, and Transmission (IEEE, 2006), pp. 97–104.

Curless, B.

L. Zhang, B. Curless, and S. M. Seitz, “Rapid shape acquisition using color structured light and multi-pass dynamic programming,” in IEEE Symposium on 3D Data Processing, Visualization, and Transmission (IEEE, 2002), pp. 24–36.
[CrossRef]

Davis, J.

J. Davis, R. Ramamoorthi, and S. Rusinkiewicz, “Spacetime stereo: a unifying framework for depth from triangulation,” in IEEE Conference on Computer Vision and Pattern Recognition (CVPR’03) (IEEE, 2003), Vol. 2, pp. 359–366.

Dekiff, M.

M. Dekiff, G. Bischoff, Z. Borocz, D. Dirksen, G. von Bally, and C. Denz, “3d-formerfassung mittels korrelation projizierter specklemuster,” in Deutsche Gesellschaft für angewandte Optik Proceedings (European Optical Society, 2008).

Denz, C.

M. Dekiff, G. Bischoff, Z. Borocz, D. Dirksen, G. von Bally, and C. Denz, “3d-formerfassung mittels korrelation projizierter specklemuster,” in Deutsche Gesellschaft für angewandte Optik Proceedings (European Optical Society, 2008).

Dirksen, D.

M. Dekiff, G. Bischoff, Z. Borocz, D. Dirksen, G. von Bally, and C. Denz, “3d-formerfassung mittels korrelation projizierter specklemuster,” in Deutsche Gesellschaft für angewandte Optik Proceedings (European Optical Society, 2008).

Garcia, R.

J. Pags, J. Salvi, R. Garcia, and C. Matabosch, “Overview of coded light projection techniques for automatic 3D profiling,” in IEEE Robotics and Automation (ICRA’03) (IEEE, 2003), Vol. 1, pp. 133–138.

Garibaldi, J.

H. Hirschmller, P. R. Innocent, and J. Garibaldi, “Real-time correlation-based stereo vision with reduced border errors,” Int. J. Comput. Vis. 47, 229–246 (2002).
[CrossRef]

Geng, Z. J.

Z. J. Geng, “Rainbow 3-D camera: new concept of high-speed three vision system,” Opt. Eng. 35, 376–383 (1996).
[CrossRef]

Gool, L. V.

T. Weise, B. Leibe, and L. V. Gool, “Fast 3D scanning with automatic motion compensation,” in IEEE Conference on Computer Vision and Pattern Recognition (CVPR’07) (IEEE, 2007), pp. 1–8.
[CrossRef]

Grosse, M.

M. Grosse and R. Kowarschik, “Space-time multiplexing in a stereo-photogrammetry setup,” in Fringe 2009, W.Osten and M.Kujawinska, eds. (Springer, 2009), pp. 755–759.

M. Grosse, “Disturbing moiré effects in a stereo-photogrammetry setup,” in Deutsche Gesellschaft für angewandte Optik Proceedings (European Optical Society, 2009).

Guo, H.

H. Guo and P. Huang, “3-D shape measurement by use of a modified Fourier transform method,” Proc. SPIE 7066, 70660E (2008).
[CrossRef]

Hall-Holt, O.

S. Rusinkiewicz, O. Hall-Holt, and M. Levoy, “Real-time 3D model acquisition,” in SIGGRAPH 2002 Proceedings (ACM, 2002), Vol. 21, pp. 438–446.
[CrossRef]

Harding, K. G.

K. G. Harding, “Phase grating use for slop discrimination in moiré contouring,” Proc. SPIE 1614, 265–270 (1992).
[CrossRef]

Hartley, R. I.

R. I. Hartley, “In defense of the 8-point algorithm,” IEEE Trans. Pattern Anal. Machine Intell. 19, 580–593 (1997).
[CrossRef]

Hirschmller, H.

H. Hirschmller, P. R. Innocent, and J. Garibaldi, “Real-time correlation-based stereo vision with reduced border errors,” Int. J. Comput. Vis. 47, 229–246 (2002).
[CrossRef]

Huang, P.

H. Guo and P. Huang, “3-D shape measurement by use of a modified Fourier transform method,” Proc. SPIE 7066, 70660E (2008).
[CrossRef]

Innocent, P. R.

H. Hirschmller, P. R. Innocent, and J. Garibaldi, “Real-time correlation-based stereo vision with reduced border errors,” Int. J. Comput. Vis. 47, 229–246 (2002).
[CrossRef]

Keriven, R.

J. Mairal, R. Keriven, and A. Chariot, “Fast and efficient dense variational stereo on GPU,” in Proceedings of International Symposium on 3D Data Processing, Visualization, and Transmission (IEEE, 2006), pp. 97–104.

Kowarschik, R.

A. Wiegmann, H. Wagner, and R. Kowarschik, “Human face measurement by projecting bandlimited random patterns,” Opt. Express 14, 7692–7698 (2006).
[CrossRef] [PubMed]

H. Wagner, A. Wiegmann, R. Kowarschik, and F. Zollner, “3D measurement of human face by stereophotogrammetry,” Proc. SPIE 5856, 509–516 (2005).
[CrossRef]

M. Grosse and R. Kowarschik, “Space-time multiplexing in a stereo-photogrammetry setup,” in Fringe 2009, W.Osten and M.Kujawinska, eds. (Springer, 2009), pp. 755–759.

Leibe, B.

T. Weise, B. Leibe, and L. V. Gool, “Fast 3D scanning with automatic motion compensation,” in IEEE Conference on Computer Vision and Pattern Recognition (CVPR’07) (IEEE, 2007), pp. 1–8.
[CrossRef]

Levoy, M.

S. Rusinkiewicz, O. Hall-Holt, and M. Levoy, “Real-time 3D model acquisition,” in SIGGRAPH 2002 Proceedings (ACM, 2002), Vol. 21, pp. 438–446.
[CrossRef]

Lewis, J. P.

J. P. Lewis, “Fast normalized-cross-correlation,” in Vision Interface (ACM, 1995).

Mairal, J.

J. Mairal, R. Keriven, and A. Chariot, “Fast and efficient dense variational stereo on GPU,” in Proceedings of International Symposium on 3D Data Processing, Visualization, and Transmission (IEEE, 2006), pp. 97–104.

Marshall, S. J.

J. P. Siebert and S. J. Marshall, “Human body 3D imaging by speckle texture projection photogrammetry,” Sensor Rev. 20, 218–226 (2000).
[CrossRef]

Matabosch, C.

J. Pags, J. Salvi, R. Garcia, and C. Matabosch, “Overview of coded light projection techniques for automatic 3D profiling,” in IEEE Robotics and Automation (ICRA’03) (IEEE, 2003), Vol. 1, pp. 133–138.

Michaelis, B.

B. Michaelis and P. Albrecht, “Stereo photogrammetry with improved spatial resolution,” in 14th International Conference on Pattern Recognition (IEEE, 1998), pp. 845–849.

Mutoh, K.

Pags, J.

J. Pags, J. Salvi, R. Garcia, and C. Matabosch, “Overview of coded light projection techniques for automatic 3D profiling,” in IEEE Robotics and Automation (ICRA’03) (IEEE, 2003), Vol. 1, pp. 133–138.

Pollefeys, M.

R. Yang, L. Wang, G. Welch, and M. Pollefeys, “Stereo vision on GPU,” in Workshop on Edge Computing Using New Commodity Architectures (University of North Carolina, 2006).

Ramamoorthi, R.

J. Davis, R. Ramamoorthi, and S. Rusinkiewicz, “Spacetime stereo: a unifying framework for depth from triangulation,” in IEEE Conference on Computer Vision and Pattern Recognition (CVPR’03) (IEEE, 2003), Vol. 2, pp. 359–366.

Royer, D.

Rusinkiewicz, S.

S. Rusinkiewicz, O. Hall-Holt, and M. Levoy, “Real-time 3D model acquisition,” in SIGGRAPH 2002 Proceedings (ACM, 2002), Vol. 21, pp. 438–446.
[CrossRef]

J. Davis, R. Ramamoorthi, and S. Rusinkiewicz, “Spacetime stereo: a unifying framework for depth from triangulation,” in IEEE Conference on Computer Vision and Pattern Recognition (CVPR’03) (IEEE, 2003), Vol. 2, pp. 359–366.

Salvi, J.

J. Pags, J. Salvi, R. Garcia, and C. Matabosch, “Overview of coded light projection techniques for automatic 3D profiling,” in IEEE Robotics and Automation (ICRA’03) (IEEE, 2003), Vol. 1, pp. 133–138.

Seitz, S. M.

L. Zhang, B. Curless, and S. M. Seitz, “Rapid shape acquisition using color structured light and multi-pass dynamic programming,” in IEEE Symposium on 3D Data Processing, Visualization, and Transmission (IEEE, 2002), pp. 24–36.
[CrossRef]

Siebert, J. P.

J. P. Siebert and S. J. Marshall, “Human body 3D imaging by speckle texture projection photogrammetry,” Sensor Rev. 20, 218–226 (2000).
[CrossRef]

Takeda, M.

von Bally, G.

M. Dekiff, G. Bischoff, Z. Borocz, D. Dirksen, G. von Bally, and C. Denz, “3d-formerfassung mittels korrelation projizierter specklemuster,” in Deutsche Gesellschaft für angewandte Optik Proceedings (European Optical Society, 2008).

Wagner, H.

A. Wiegmann, H. Wagner, and R. Kowarschik, “Human face measurement by projecting bandlimited random patterns,” Opt. Express 14, 7692–7698 (2006).
[CrossRef] [PubMed]

H. Wagner, A. Wiegmann, R. Kowarschik, and F. Zollner, “3D measurement of human face by stereophotogrammetry,” Proc. SPIE 5856, 509–516 (2005).
[CrossRef]

Wang, L.

R. Yang, L. Wang, G. Welch, and M. Pollefeys, “Stereo vision on GPU,” in Workshop on Edge Computing Using New Commodity Architectures (University of North Carolina, 2006).

Weise, T.

T. Weise, B. Leibe, and L. V. Gool, “Fast 3D scanning with automatic motion compensation,” in IEEE Conference on Computer Vision and Pattern Recognition (CVPR’07) (IEEE, 2007), pp. 1–8.
[CrossRef]

Welch, G.

R. Yang, L. Wang, G. Welch, and M. Pollefeys, “Stereo vision on GPU,” in Workshop on Edge Computing Using New Commodity Architectures (University of North Carolina, 2006).

Wiegmann, A.

A. Wiegmann, H. Wagner, and R. Kowarschik, “Human face measurement by projecting bandlimited random patterns,” Opt. Express 14, 7692–7698 (2006).
[CrossRef] [PubMed]

H. Wagner, A. Wiegmann, R. Kowarschik, and F. Zollner, “3D measurement of human face by stereophotogrammetry,” Proc. SPIE 5856, 509–516 (2005).
[CrossRef]

Wust, C.

C. Wust and D. W. Capson, “Surface profile measurement using color fringe projection,” Machine Vis. Appl. 4, 193–203(1991).
[CrossRef]

Yang, R.

R. Yang, L. Wang, G. Welch, and M. Pollefeys, “Stereo vision on GPU,” in Workshop on Edge Computing Using New Commodity Architectures (University of North Carolina, 2006).

Yau, S.

Zhang, L.

L. Zhang, B. Curless, and S. M. Seitz, “Rapid shape acquisition using color structured light and multi-pass dynamic programming,” in IEEE Symposium on 3D Data Processing, Visualization, and Transmission (IEEE, 2002), pp. 24–36.
[CrossRef]

Zhang, S.

S. Zhang, “Recent progresses on real-time 3D shape measurement using digital fringe projection techniques,” Opt. Lasers Eng. 48, 149–158 (2010).
[CrossRef]

S. Zhang, D. Royer, and S. Yau, “GPU-assisted high-resolution, real-time 3-D shape measurement,” Opt. Express 14, 9120–9129 (2006).
[CrossRef] [PubMed]

S. Zhang, “High-resolution, real-time 3-D shape measurement,” Ph.D. dissertation (Stony Brook University, 2005).

Zhang, Z.

Z. Zhang, “A flexible new technique for camera calibration,” Tech. Rep. MSR-TR-98-71 (Microsoft Research, 1998).

Zollner, F.

H. Wagner, A. Wiegmann, R. Kowarschik, and F. Zollner, “3D measurement of human face by stereophotogrammetry,” Proc. SPIE 5856, 509–516 (2005).
[CrossRef]

Appl. Opt. (1)

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

R. I. Hartley, “In defense of the 8-point algorithm,” IEEE Trans. Pattern Anal. Machine Intell. 19, 580–593 (1997).
[CrossRef]

Int. J. Comput. Vis. (1)

H. Hirschmller, P. R. Innocent, and J. Garibaldi, “Real-time correlation-based stereo vision with reduced border errors,” Int. J. Comput. Vis. 47, 229–246 (2002).
[CrossRef]

Machine Vis. Appl. (1)

C. Wust and D. W. Capson, “Surface profile measurement using color fringe projection,” Machine Vis. Appl. 4, 193–203(1991).
[CrossRef]

Opt. Eng. (1)

Z. J. Geng, “Rainbow 3-D camera: new concept of high-speed three vision system,” Opt. Eng. 35, 376–383 (1996).
[CrossRef]

Opt. Express (2)

Opt. Lasers Eng. (1)

S. Zhang, “Recent progresses on real-time 3D shape measurement using digital fringe projection techniques,” Opt. Lasers Eng. 48, 149–158 (2010).
[CrossRef]

Proc. SPIE (3)

K. G. Harding, “Phase grating use for slop discrimination in moiré contouring,” Proc. SPIE 1614, 265–270 (1992).
[CrossRef]

H. Guo and P. Huang, “3-D shape measurement by use of a modified Fourier transform method,” Proc. SPIE 7066, 70660E (2008).
[CrossRef]

H. Wagner, A. Wiegmann, R. Kowarschik, and F. Zollner, “3D measurement of human face by stereophotogrammetry,” Proc. SPIE 5856, 509–516 (2005).
[CrossRef]

Sensor Rev. (1)

J. P. Siebert and S. J. Marshall, “Human body 3D imaging by speckle texture projection photogrammetry,” Sensor Rev. 20, 218–226 (2000).
[CrossRef]

Other (16)

M. Dekiff, G. Bischoff, Z. Borocz, D. Dirksen, G. von Bally, and C. Denz, “3d-formerfassung mittels korrelation projizierter specklemuster,” in Deutsche Gesellschaft für angewandte Optik Proceedings (European Optical Society, 2008).

M. Grosse and R. Kowarschik, “Space-time multiplexing in a stereo-photogrammetry setup,” in Fringe 2009, W.Osten and M.Kujawinska, eds. (Springer, 2009), pp. 755–759.

J. P. Lewis, “Fast normalized-cross-correlation,” in Vision Interface (ACM, 1995).

B. Michaelis and P. Albrecht, “Stereo photogrammetry with improved spatial resolution,” in 14th International Conference on Pattern Recognition (IEEE, 1998), pp. 845–849.

S. Rusinkiewicz, O. Hall-Holt, and M. Levoy, “Real-time 3D model acquisition,” in SIGGRAPH 2002 Proceedings (ACM, 2002), Vol. 21, pp. 438–446.
[CrossRef]

L. Zhang, B. Curless, and S. M. Seitz, “Rapid shape acquisition using color structured light and multi-pass dynamic programming,” in IEEE Symposium on 3D Data Processing, Visualization, and Transmission (IEEE, 2002), pp. 24–36.
[CrossRef]

T. Weise, B. Leibe, and L. V. Gool, “Fast 3D scanning with automatic motion compensation,” in IEEE Conference on Computer Vision and Pattern Recognition (CVPR’07) (IEEE, 2007), pp. 1–8.
[CrossRef]

R. Yang, L. Wang, G. Welch, and M. Pollefeys, “Stereo vision on GPU,” in Workshop on Edge Computing Using New Commodity Architectures (University of North Carolina, 2006).

J. Pags, J. Salvi, R. Garcia, and C. Matabosch, “Overview of coded light projection techniques for automatic 3D profiling,” in IEEE Robotics and Automation (ICRA’03) (IEEE, 2003), Vol. 1, pp. 133–138.

Z. Zhang, “A flexible new technique for camera calibration,” Tech. Rep. MSR-TR-98-71 (Microsoft Research, 1998).

J. Davis, R. Ramamoorthi, and S. Rusinkiewicz, “Spacetime stereo: a unifying framework for depth from triangulation,” in IEEE Conference on Computer Vision and Pattern Recognition (CVPR’03) (IEEE, 2003), Vol. 2, pp. 359–366.

J. Mairal, R. Keriven, and A. Chariot, “Fast and efficient dense variational stereo on GPU,” in Proceedings of International Symposium on 3D Data Processing, Visualization, and Transmission (IEEE, 2006), pp. 97–104.

J.C.Dainty, ed., Laser Speckle and Related Phenomena (Springer Verlag, 1984).

M. Grosse, “Disturbing moiré effects in a stereo-photogrammetry setup,” in Deutsche Gesellschaft für angewandte Optik Proceedings (European Optical Society, 2009).

S. Zhang, “High-resolution, real-time 3-D shape measurement,” Ph.D. dissertation (Stony Brook University, 2005).

Centre Suisse d’Electronique et de Microtechnique, “Time of flight camera technology,” Tech. Rep. (Centre Suisse d’Electronique et de Microtechnique, 2009).

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Figures (13)

Fig. 1
Fig. 1

Reference stereo setup.

Fig. 2
Fig. 2

Two BLP out of a sequence of N BLP patterns, which are projected onto the object per measurement via the DLP.

Fig. 3
Fig. 3

Results of two 3D measurements of human faces using the reference setup.

Fig. 4
Fig. 4

Setup consisting of laser, diffuser (D), step motor (M), lens (L), and object.

Fig. 5
Fig. 5

Images from left to right: plane with DLP-pattern, plane with speckle pattern, sphere ( r = 1.52 cm ) with DLP pattern, and sphere with speckle pattern.

Fig. 6
Fig. 6

Reconstructed 3D time sequence of a human face in motion.

Fig. 7
Fig. 7

Standard deviation of measured 3D points to a fitted plane (dot, speckle; square, DLP) for different sequence lengths.

Fig. 8
Fig. 8

Ratio of correct correspondences to total correspondences of the plane measurement (dot, speckle; square, DLP).

Fig. 9
Fig. 9

Standard deviation of measured 3D points to a fitted sphere (dot, speckle; square, DLP) for different sequence lengths.

Fig. 10
Fig. 10

Reconstruction of the sample plane using a sequence length of 30 images, only the illumination source was changed between measurements; left, DLP system; right, speckle system.

Fig. 11
Fig. 11

Total number of correct correspondences (dot, speckle; square, DLP).

Fig. 12
Fig. 12

Relative amount of trustworthy points for different plane speed (dot, speckle; square, DLP).

Fig. 13
Fig. 13

Plane aberration of the reconstructed plane for different speed (dot, speckle; square, DLP).

Tables (1)

Tables Icon

Table 1 Comparison of Uncertainty of Measurement for Four Setups a

Equations (4)

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

ρ ( i , j , i , j ) = l = n x n x k = n y n y ( g ( i + l , j + k ) g ¯ ) ( g ( i + l , j + k ) g ¯ ) l = n x n x k = n y n y ( g ( i + l , j + k ) g ¯ ) 2 l = n x n x k = n y n y ( g ( i + l , j + k ) g ¯ ) 2 ,
ρ ( i , j , i , j ) = t = 1 N ( g ( i , j , t ) g ¯ ) ( g ( i , j , t ) g ¯ ) t = 1 N ( g ( i , j , t ) g ¯ ) 2 t = 1 N ( g ( i , j , t ) g ¯ ) 2 ,
L = 0.61 λ f A ,
s = λ z 2 L

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