Abstract

Active triangulation measurement systems with a rigid geometric configuration are inappropriate for scanning large objects with low measuring tolerances. The reason is that the ratio between the depth recovery error and the lateral extension is a constant that depends on the geometric setup. As a consequence, measuring large areas with low depth recovery error requires the use of multiresolution techniques. We propose a multiresolution technique based on a camera–projector system previously calibrated. The method consists of changing the camera or projector’s parameters in order to increase the system depth sensitivity. A subpixel retroprojection error in the self-calibration process and a decrease of approximately one order of magnitude in the depth recovery error can be achieved using the proposed method.

© 2009 Optical Society of America

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References

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  1. J. Pages, J. Salvi, R. Garcia, and C. Matabosch, “Overview of coded light projection techniques for automatic 3D profiling,” in Proceedings of the IEEE International Conference on Robotics and Automation (IEEE, 2003), Vol. 1, pp. 133-138.
  2. H. Steinbichler, E. H. Nösekabel, and R. Rösch, “Optical inspection in the production line,” in Fringe 2001--4th International Workshop on Automatic Processing of Fringe Patterns, W. Osten and W. Jüptner, eds. (Data Science Library, Elsevier, 2001), pp. 587-592.
  3. G. Notni, “360 deg shape measurement with fringe projection--calibration and application, ” in Fringe 2001--4th International Workshop on Automatic Processing of Fringe Patterns, W. Osten and W. Jüptner, eds. (Data Science Library, Elsevier, 2001), pp. 311-323.
  4. G. Wiora, “High resolution measurement of phase-shift amplitude and numeric object phase calculation,” Proc. SPIE 4117, 289-299 (2000).
    [CrossRef]
  5. D. Kayser, T. Bothe, and W. Osten, “Scaled topometry in a multisensor approach,” Opt. Eng. 43, 2469-2477(2004).
    [CrossRef]
  6. P. Andrä, E. Ivanov, and W. Osten, “Scaled topometry--an active measurement approach for wide scale 3D surface inspection,” in Fringe 1997: 3rd International Workshop on Automatic Processing of Fringe Patterns, W. Osten and W. Jüptner, eds. (Akademie-Verlag, 1997), pp. 179-189.
  7. D. Kayser, T. Bothe, and W. Osten, “Fault detection in gray-value images of surfaces on different scales,” Proc. SPIE 3744, 110-117 (1999).
    [CrossRef]
  8. W. Osten, P. Andrä, and D. Kayser, “Highly-resolved measurement of extended technical surfaces with scalable topometry,” Tech. Mess. ATM 66, 413-428 (1999).
  9. J. Vargas and J. A. Quiroga, “A novel multiresolution approach for an adaptable structured light,” Opt. Eng. 47, 023601 (2008).
    [CrossRef]
  10. M. Fiala, “Artag, an improved marker system based on artoolkit,” in National Research Council Publication47166/ERB-1111 (2004).
  11. W. Schereiber and G. Notni, “Theory and arrangements of self-calibrating whole-body three-dimensional measurement systems using fringe projection technique,” Opt. Eng. 39, 159-169 (2000).
    [CrossRef]
  12. S. Y. Chen and Y. F. Li, “Self recalibration of a structured light vision system from a single view,” in Proceedings of the IEEE International Conference on Robotics and Automation, Washington DC, (IEEE, 2002), pp. 2539-2544.
  13. Y. F. Lie and Y. Chen, “Automatic recalibration of an active structured light vision system,” IEEE Trans. Robot. Autom. 19, 259-568 (2003).
    [CrossRef]
  14. R. Hartley and A. Zisserman, Multiple View Geometry in Computer Vision (Cambridge University, 2004).
    [CrossRef]
  15. R. Legarda-Sáenz, T. Bothe, and W. Jüptner, “Accurate procedure for calibration of a structured light system,” Opt. Eng. 43, 464-471 (2004).
    [CrossRef]
  16. J. Heikkilä, “Geometrical camera calibration using circular control points,” IEEE Trans. Pattern Anal. Mach. Intell. 22, 1066-1077 (2000).
    [CrossRef]
  17. O. Faugueras, Three-Dimensional Computer Vision: A Geometric Viewpoint (MIT, 1993).

2008 (1)

J. Vargas and J. A. Quiroga, “A novel multiresolution approach for an adaptable structured light,” Opt. Eng. 47, 023601 (2008).
[CrossRef]

2004 (2)

D. Kayser, T. Bothe, and W. Osten, “Scaled topometry in a multisensor approach,” Opt. Eng. 43, 2469-2477(2004).
[CrossRef]

R. Legarda-Sáenz, T. Bothe, and W. Jüptner, “Accurate procedure for calibration of a structured light system,” Opt. Eng. 43, 464-471 (2004).
[CrossRef]

2003 (1)

Y. F. Lie and Y. Chen, “Automatic recalibration of an active structured light vision system,” IEEE Trans. Robot. Autom. 19, 259-568 (2003).
[CrossRef]

2000 (3)

G. Wiora, “High resolution measurement of phase-shift amplitude and numeric object phase calculation,” Proc. SPIE 4117, 289-299 (2000).
[CrossRef]

J. Heikkilä, “Geometrical camera calibration using circular control points,” IEEE Trans. Pattern Anal. Mach. Intell. 22, 1066-1077 (2000).
[CrossRef]

W. Schereiber and G. Notni, “Theory and arrangements of self-calibrating whole-body three-dimensional measurement systems using fringe projection technique,” Opt. Eng. 39, 159-169 (2000).
[CrossRef]

1999 (2)

D. Kayser, T. Bothe, and W. Osten, “Fault detection in gray-value images of surfaces on different scales,” Proc. SPIE 3744, 110-117 (1999).
[CrossRef]

W. Osten, P. Andrä, and D. Kayser, “Highly-resolved measurement of extended technical surfaces with scalable topometry,” Tech. Mess. ATM 66, 413-428 (1999).

Andrä, P.

W. Osten, P. Andrä, and D. Kayser, “Highly-resolved measurement of extended technical surfaces with scalable topometry,” Tech. Mess. ATM 66, 413-428 (1999).

P. Andrä, E. Ivanov, and W. Osten, “Scaled topometry--an active measurement approach for wide scale 3D surface inspection,” in Fringe 1997: 3rd International Workshop on Automatic Processing of Fringe Patterns, W. Osten and W. Jüptner, eds. (Akademie-Verlag, 1997), pp. 179-189.

Bothe, T.

R. Legarda-Sáenz, T. Bothe, and W. Jüptner, “Accurate procedure for calibration of a structured light system,” Opt. Eng. 43, 464-471 (2004).
[CrossRef]

D. Kayser, T. Bothe, and W. Osten, “Scaled topometry in a multisensor approach,” Opt. Eng. 43, 2469-2477(2004).
[CrossRef]

D. Kayser, T. Bothe, and W. Osten, “Fault detection in gray-value images of surfaces on different scales,” Proc. SPIE 3744, 110-117 (1999).
[CrossRef]

Chen, S. Y.

S. Y. Chen and Y. F. Li, “Self recalibration of a structured light vision system from a single view,” in Proceedings of the IEEE International Conference on Robotics and Automation, Washington DC, (IEEE, 2002), pp. 2539-2544.

Chen, Y.

Y. F. Lie and Y. Chen, “Automatic recalibration of an active structured light vision system,” IEEE Trans. Robot. Autom. 19, 259-568 (2003).
[CrossRef]

Faugueras, O.

O. Faugueras, Three-Dimensional Computer Vision: A Geometric Viewpoint (MIT, 1993).

Fiala, M.

M. Fiala, “Artag, an improved marker system based on artoolkit,” in National Research Council Publication47166/ERB-1111 (2004).

Garcia, R.

J. Pages, J. Salvi, R. Garcia, and C. Matabosch, “Overview of coded light projection techniques for automatic 3D profiling,” in Proceedings of the IEEE International Conference on Robotics and Automation (IEEE, 2003), Vol. 1, pp. 133-138.

Hartley, R.

R. Hartley and A. Zisserman, Multiple View Geometry in Computer Vision (Cambridge University, 2004).
[CrossRef]

Heikkilä, J.

J. Heikkilä, “Geometrical camera calibration using circular control points,” IEEE Trans. Pattern Anal. Mach. Intell. 22, 1066-1077 (2000).
[CrossRef]

Ivanov, E.

P. Andrä, E. Ivanov, and W. Osten, “Scaled topometry--an active measurement approach for wide scale 3D surface inspection,” in Fringe 1997: 3rd International Workshop on Automatic Processing of Fringe Patterns, W. Osten and W. Jüptner, eds. (Akademie-Verlag, 1997), pp. 179-189.

Jüptner, W.

R. Legarda-Sáenz, T. Bothe, and W. Jüptner, “Accurate procedure for calibration of a structured light system,” Opt. Eng. 43, 464-471 (2004).
[CrossRef]

Kayser, D.

D. Kayser, T. Bothe, and W. Osten, “Scaled topometry in a multisensor approach,” Opt. Eng. 43, 2469-2477(2004).
[CrossRef]

D. Kayser, T. Bothe, and W. Osten, “Fault detection in gray-value images of surfaces on different scales,” Proc. SPIE 3744, 110-117 (1999).
[CrossRef]

W. Osten, P. Andrä, and D. Kayser, “Highly-resolved measurement of extended technical surfaces with scalable topometry,” Tech. Mess. ATM 66, 413-428 (1999).

Legarda-Sáenz, R.

R. Legarda-Sáenz, T. Bothe, and W. Jüptner, “Accurate procedure for calibration of a structured light system,” Opt. Eng. 43, 464-471 (2004).
[CrossRef]

Li, Y. F.

S. Y. Chen and Y. F. Li, “Self recalibration of a structured light vision system from a single view,” in Proceedings of the IEEE International Conference on Robotics and Automation, Washington DC, (IEEE, 2002), pp. 2539-2544.

Lie, Y. F.

Y. F. Lie and Y. Chen, “Automatic recalibration of an active structured light vision system,” IEEE Trans. Robot. Autom. 19, 259-568 (2003).
[CrossRef]

Matabosch, C.

J. Pages, J. Salvi, R. Garcia, and C. Matabosch, “Overview of coded light projection techniques for automatic 3D profiling,” in Proceedings of the IEEE International Conference on Robotics and Automation (IEEE, 2003), Vol. 1, pp. 133-138.

Nösekabel, E. H.

H. Steinbichler, E. H. Nösekabel, and R. Rösch, “Optical inspection in the production line,” in Fringe 2001--4th International Workshop on Automatic Processing of Fringe Patterns, W. Osten and W. Jüptner, eds. (Data Science Library, Elsevier, 2001), pp. 587-592.

Notni, G.

W. Schereiber and G. Notni, “Theory and arrangements of self-calibrating whole-body three-dimensional measurement systems using fringe projection technique,” Opt. Eng. 39, 159-169 (2000).
[CrossRef]

G. Notni, “360 deg shape measurement with fringe projection--calibration and application, ” in Fringe 2001--4th International Workshop on Automatic Processing of Fringe Patterns, W. Osten and W. Jüptner, eds. (Data Science Library, Elsevier, 2001), pp. 311-323.

Osten, W.

D. Kayser, T. Bothe, and W. Osten, “Scaled topometry in a multisensor approach,” Opt. Eng. 43, 2469-2477(2004).
[CrossRef]

D. Kayser, T. Bothe, and W. Osten, “Fault detection in gray-value images of surfaces on different scales,” Proc. SPIE 3744, 110-117 (1999).
[CrossRef]

W. Osten, P. Andrä, and D. Kayser, “Highly-resolved measurement of extended technical surfaces with scalable topometry,” Tech. Mess. ATM 66, 413-428 (1999).

P. Andrä, E. Ivanov, and W. Osten, “Scaled topometry--an active measurement approach for wide scale 3D surface inspection,” in Fringe 1997: 3rd International Workshop on Automatic Processing of Fringe Patterns, W. Osten and W. Jüptner, eds. (Akademie-Verlag, 1997), pp. 179-189.

Pages, J.

J. Pages, J. Salvi, R. Garcia, and C. Matabosch, “Overview of coded light projection techniques for automatic 3D profiling,” in Proceedings of the IEEE International Conference on Robotics and Automation (IEEE, 2003), Vol. 1, pp. 133-138.

Quiroga, J. A.

J. Vargas and J. A. Quiroga, “A novel multiresolution approach for an adaptable structured light,” Opt. Eng. 47, 023601 (2008).
[CrossRef]

Rösch, R.

H. Steinbichler, E. H. Nösekabel, and R. Rösch, “Optical inspection in the production line,” in Fringe 2001--4th International Workshop on Automatic Processing of Fringe Patterns, W. Osten and W. Jüptner, eds. (Data Science Library, Elsevier, 2001), pp. 587-592.

Salvi, J.

J. Pages, J. Salvi, R. Garcia, and C. Matabosch, “Overview of coded light projection techniques for automatic 3D profiling,” in Proceedings of the IEEE International Conference on Robotics and Automation (IEEE, 2003), Vol. 1, pp. 133-138.

Schereiber, W.

W. Schereiber and G. Notni, “Theory and arrangements of self-calibrating whole-body three-dimensional measurement systems using fringe projection technique,” Opt. Eng. 39, 159-169 (2000).
[CrossRef]

Steinbichler, H.

H. Steinbichler, E. H. Nösekabel, and R. Rösch, “Optical inspection in the production line,” in Fringe 2001--4th International Workshop on Automatic Processing of Fringe Patterns, W. Osten and W. Jüptner, eds. (Data Science Library, Elsevier, 2001), pp. 587-592.

Vargas, J.

J. Vargas and J. A. Quiroga, “A novel multiresolution approach for an adaptable structured light,” Opt. Eng. 47, 023601 (2008).
[CrossRef]

Wiora, G.

G. Wiora, “High resolution measurement of phase-shift amplitude and numeric object phase calculation,” Proc. SPIE 4117, 289-299 (2000).
[CrossRef]

Zisserman, A.

R. Hartley and A. Zisserman, Multiple View Geometry in Computer Vision (Cambridge University, 2004).
[CrossRef]

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

J. Heikkilä, “Geometrical camera calibration using circular control points,” IEEE Trans. Pattern Anal. Mach. Intell. 22, 1066-1077 (2000).
[CrossRef]

IEEE Trans. Robot. Autom. (1)

Y. F. Lie and Y. Chen, “Automatic recalibration of an active structured light vision system,” IEEE Trans. Robot. Autom. 19, 259-568 (2003).
[CrossRef]

Opt. Eng. (4)

W. Schereiber and G. Notni, “Theory and arrangements of self-calibrating whole-body three-dimensional measurement systems using fringe projection technique,” Opt. Eng. 39, 159-169 (2000).
[CrossRef]

R. Legarda-Sáenz, T. Bothe, and W. Jüptner, “Accurate procedure for calibration of a structured light system,” Opt. Eng. 43, 464-471 (2004).
[CrossRef]

D. Kayser, T. Bothe, and W. Osten, “Scaled topometry in a multisensor approach,” Opt. Eng. 43, 2469-2477(2004).
[CrossRef]

J. Vargas and J. A. Quiroga, “A novel multiresolution approach for an adaptable structured light,” Opt. Eng. 47, 023601 (2008).
[CrossRef]

Proc. SPIE (2)

D. Kayser, T. Bothe, and W. Osten, “Fault detection in gray-value images of surfaces on different scales,” Proc. SPIE 3744, 110-117 (1999).
[CrossRef]

G. Wiora, “High resolution measurement of phase-shift amplitude and numeric object phase calculation,” Proc. SPIE 4117, 289-299 (2000).
[CrossRef]

Tech. Mess. ATM (1)

W. Osten, P. Andrä, and D. Kayser, “Highly-resolved measurement of extended technical surfaces with scalable topometry,” Tech. Mess. ATM 66, 413-428 (1999).

Other (8)

M. Fiala, “Artag, an improved marker system based on artoolkit,” in National Research Council Publication47166/ERB-1111 (2004).

P. Andrä, E. Ivanov, and W. Osten, “Scaled topometry--an active measurement approach for wide scale 3D surface inspection,” in Fringe 1997: 3rd International Workshop on Automatic Processing of Fringe Patterns, W. Osten and W. Jüptner, eds. (Akademie-Verlag, 1997), pp. 179-189.

J. Pages, J. Salvi, R. Garcia, and C. Matabosch, “Overview of coded light projection techniques for automatic 3D profiling,” in Proceedings of the IEEE International Conference on Robotics and Automation (IEEE, 2003), Vol. 1, pp. 133-138.

H. Steinbichler, E. H. Nösekabel, and R. Rösch, “Optical inspection in the production line,” in Fringe 2001--4th International Workshop on Automatic Processing of Fringe Patterns, W. Osten and W. Jüptner, eds. (Data Science Library, Elsevier, 2001), pp. 587-592.

G. Notni, “360 deg shape measurement with fringe projection--calibration and application, ” in Fringe 2001--4th International Workshop on Automatic Processing of Fringe Patterns, W. Osten and W. Jüptner, eds. (Data Science Library, Elsevier, 2001), pp. 311-323.

O. Faugueras, Three-Dimensional Computer Vision: A Geometric Viewpoint (MIT, 1993).

S. Y. Chen and Y. F. Li, “Self recalibration of a structured light vision system from a single view,” in Proceedings of the IEEE International Conference on Robotics and Automation, Washington DC, (IEEE, 2002), pp. 2539-2544.

R. Hartley and A. Zisserman, Multiple View Geometry in Computer Vision (Cambridge University, 2004).
[CrossRef]

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Figures (6)

Fig. 1
Fig. 1

Scheme of the process shown in Subsection 2B, where C is the camera, P is the projector, and P is the projector before changing its internal and external parameters. M C is an arbitrary point, and m P , m C , and m P correspond to its projection in the projector (P), camera (C), and projector ( P ) frames.

Fig. 2
Fig. 2

Scheme of the process shown in Subsection 2C, where C is the camera, P is the projector, and C is the camera before changing its internal and external parameters. M P is an arbitrary point that it is “observed” by m C and m P . M P is another arbitrary point that it is “observed” by m C and m P .

Fig. 3
Fig. 3

Heikkila’s 3D data set points, referred to in the camera reference system, used in the self-calibration process simulation. There are 491 3D points distributed in two planes with a 90 ° angle between them.

Fig. 4
Fig. 4

Metallic step pyramid used to test the purposed multiresolution technique. The different step values are indicated. The broken dark line shows the 180 pixel row.

Fig. 5
Fig. 5

Depth profile along the 180 px row of the step pyramid obtained with the C P , C P , and C P configurations.

Fig. 6
Fig. 6

Depth profile of the metallic pyramid central region to observe the 0.1 mm smallest step obtained with the C P , C P , and C P configurations.

Tables (4)

Tables Icon

Table 1 Camera Calibration Parameters Obtained Using the Zhang Calibration Approach and Our Self-Calibration Method a

Tables Icon

Table 2 Retroprojected Errors Using the Zhang Calibration Method and Our Self-Calibration Engine

Tables Icon

Table 3 Values of the Different Depth Steps (b, c, and d in Fig. 5) Obtained from the C P , C P , and C P Configurations

Tables Icon

Table 4 Computed Root Mean Square Error Obtained in the Plane Central Region of the Step Pyramid between the Best Fitted Plane and the Depth Data in Every Configuration

Equations (18)

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

s m C = P C M W ,
s m P = P P M W ,
s m C = K C [ R C | t C ] M W ,
s m P = K P [ R P | t P ] M W ,
K i = ( f i X 0 C i X 0 f i Y C i Y 0 0 1 ) ,
P i = [ K i R i | K i t i ] ,
( u P , v P ) = ( Φ X T X 2 π , Φ Y T Y 2 π ) ,
( P C 3 M W ) u C = P C 1 M W , ( P C 3 M W ) v C = P C 2 M W , ( P P 3 M W ) u P = P P 1 M W , ( P P 3 M W ) v P = P P 2 M W .
A M W = 0 ,
A = ( u C P C 3 P C 1 v C P C 3 P C 2 u P P P 3 - P P 1 v P P P 3 P P 2 ) .
s m C = K C [ I | 0 ] M C ( m C ) , s m P = K P [ R | t ] M C ( m C ) ,
s m P = P P M C ( m C ) = K P [ R | t ] M C ( m C ) .
( u P P P 3 P P 1 v P P P 3 P P 2 ) M C = ( 0 0 0 0 ) .
( u P X C X C u P Y C Y C u P Z C Z C u P 1 0 0 0 0 v P X C 0 v P Y C 0 v P Z C 0 v P 0 X C Y C Z C 1 ) S P = ( 0 0 ) ,
s m C = K C [ R | t ] 1 M P ( m C ) , s m P = K P [ I | 0 ] M P ( m C ) ,
s m C = K C [ R | t ] 1 M P ( m C ) .
( u C P C 3 P C 1 v C P C 3 P C 2 ) M P ( m C ) = ( 0 0 0 0 ) .
( u C X P X P u C Y P Y P u C Z P Z P u C 1 0 0 0 0 v C X P 0 v C Y P 0 v C Z P 0 v C 0 X P Y P Z P 1 ) S C = ( 0 0 ) ,

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