Abstract

Determining the correspondence in coded structured light is challenging, but it is very important in one-shot techniques for 3D shape reconstruction. The problem of decoding stripe patterns can be modeled as matching two code sequences. We propose decoding edges indirectly based on the property of the stripe pattern, which can be represented as edge code, color code, or mixed code sequences. While traditional methods match two edge code sequences, indirect decoding matches two color sequences or mixed code sequences. The advantages of the proposed method, including a higher Hamming distance, enforced local coherence, and more code information, make indirect decoding excellent in performance. Previously, the lack of ground truth has prevented direct comparisons of different decoding algorithms. Here we obtain six benchmark datasets using the robust space–time analysis. Five decoding methods are quantitatively evaluated using the ground truth. The comparison results show that our method is robust for complex code situations and that it outperforms the state-of-the-art technique in this area.

© 2011 Optical Society of America

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  1. F. Chen, G. Brown, and M. Song, “Overview of three-dimensional shape measurement using optical methods,” Opt. Eng. 39, 10–22 (2000).
    [CrossRef]
  2. F. Blais, “Review of 20 years of range sensor development,” J. Electron. Imaging 13, 231–243 (2004).
    [CrossRef]
  3. J. Salvi, J. Pages, and J. Battle, “Pattern codification strategies in structured light systems,” Pattern Recogn. 37, 827–849 (2004).
    [CrossRef]
  4. J. Salvi, S. Fernandez, T. Pribanic, and X. Llado, “A state of the art in structured light patterns for surface profilometry,” Pattern Recogn. 43, 2666–2680 (2010).
    [CrossRef]
  5. P. Fechteler and P. Eisert, “Adaptive color classification for structured light systems,” in Proceedings of the 15th International Conference on Computer Vision and Pattern Recognition—Workshop on 3D Face Processing (IEEE, 2008), pp. 1–7.
  6. L. Zhang, B. Curless, and S. Seitz, “Rapid shape acquisition using color structured light and multi-pass dynamic programming,” in Proceedings of the 1st IEEE International Symposium on 3D Data Processing, Visualization, and Transmission (IEEE, 2002), pp. 24–36.
    [CrossRef] [PubMed]
  7. O. Hall-Holt and S. Rusinkiewicz, “Stripe boundary codes for real-time structured-light range scanning of moving objects,” in Proceedings of the Eighth IEEE International Conference on Computer Vision (IEEE, 2001), pp. 359–366.
    [CrossRef]
  8. H. Li, R. Straub, and H. Prautzsch, “Structured light based reconstruction under local spatial coherence assumption,” in Proceedings of the Third International Symposium on 3D Data Processing, Visualization, and Transmission (IEEE Computer Society, 2006), pp. 575–582.
    [CrossRef] [PubMed]
  9. C. Je, S. W. Lee, and R.-H. Park, “High-contrast color-stripe pattern for rapid structured-light range imaging,” in Proceedings of the 8th European Conference on Computer Vision (Springer, 2004), pp. 95–107.
  10. X. Zhang and L. Zhu, “Determination of edge correspondence using color codes for one-shot shape acquisition,” Opt. Lasers Eng. 49, 97–103 (2010).
    [CrossRef]
  11. H. Kawasaki, R. Furukawa, R. Sagawa, and Y. Yagi, “Dynamic scene shape reconstruction using a single structured light pattern,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (IEEE, 2008), pp. 1–8.
  12. S. Chen, Y. Li, and J. Zhang, “Vision processing for realtime 3-D data acquisition based on coded structured light,” IEEE Trans. Image Process. 17, 167–176 (2007).
    [CrossRef]
  13. J. Salvi, J. Batlle, and E. Mouaddib, “A robust-coded pattern projection for dynamic 3D scene measurement,” Pattern Recogn. Lett. 19, 1055–1065 (1998).
    [CrossRef]
  14. R. Morano, C. Ozturk, R. Conn, S. Dubin, S. Zietz, and J. Nissanov, “Structured light using pseudorandom codes,” IEEE Trans. Pattern Anal. Machine Intell. 322–327 (1998).
    [CrossRef]
  15. I. Albitar, P. Graebling, and C. Doignon, “Robust structured light coding for 3D reconstruction,” in Proceedings of the IEEE 11th International Conference on Computer Vision (IEEE, 2007), pp. 1–6.
    [CrossRef]
  16. T. Koninckx and L. Van Gool, “Real-time range acquisition by adaptive structured light,” IEEE Trans. Pattern Anal. Machine Intell. 28, 432–445 (2006).
    [CrossRef]
  17. J. Pages, J. Salvi, C. Collewet, and J. Forest, “Optimised De Bruijn patterns for one-shot shape acquisition,” Image Vis. Comput. 23, 707–720 (2005).
    [CrossRef]
  18. K. Boyer and A. Kak, “Color-encoded structured light for rapid active ranging,” IEEE Trans. Pattern Anal. Machine Intell. PAMI-9, 14–28 (1987).
    [CrossRef]
  19. T. Koninckx, I. Geys, T. Jaeggli, L. Van Gool, and B. Leuven, “A graph cut based adaptive structured light approach for real-time range acquisition,” in Proceedings of the International Symposium on 3D Data Processing, Visualization and Transmission (IEEE Computer Society, 2004), pp. 413–421.
    [CrossRef]
  20. B. Curless and M. Levoy, “Better optical triangulation through spacetime analysis,” in Proceedings of the IEEE International Conference on Computer Vision (IEEE, 1995), pp. 987–994.
    [CrossRef]
  21. H. Hügli and G. Maitre, “Generation and use of color pseudorandom sequences for coding structured light in active ranging,” Proc. SPIE 1010, 75–82 (1989).
  22. F. MacWilliams and N. Sloane, “Pseudo-random sequences and arrays,” Proc. IEEE 64, 1715–1729 (1976).
    [CrossRef]
  23. X. Zhang and L. Zhu, “Projector calibration from the camera image point of view,” Opt. Eng. 48, 117–208 (2009).
    [CrossRef]
  24. D. Caspi, N. Kiryati, and J. Shamir, “Range imaging with adaptive color structured light,” IEEE Trans. Pattern Anal. Machine Intell. 20, 470–480 (1998).
    [CrossRef]
  25. X. Zhang and L. Zhu, “Robust calibration of a color structured light system using color correction,” in Proceedings of the Intelligent Robotics and Applications Second International Conference, ICIRA 2009 (Springer, 2009), Vol.  5928, pp. 936–946.
  26. A. Cumani, “Edge detection in multispectral images,” CVGIP: Graph. Models Image Process. 53, 40–51 (1991).
    [CrossRef]
  27. C. Chen, Y. Hung, C. Chiang, and J. Wu, “Range data acquisition using color structured lighting and stereo vision,” Image Vis. Comput. 15, 445–456 (1997).
    [CrossRef]

2010

J. Salvi, S. Fernandez, T. Pribanic, and X. Llado, “A state of the art in structured light patterns for surface profilometry,” Pattern Recogn. 43, 2666–2680 (2010).
[CrossRef]

X. Zhang and L. Zhu, “Determination of edge correspondence using color codes for one-shot shape acquisition,” Opt. Lasers Eng. 49, 97–103 (2010).
[CrossRef]

2009

X. Zhang and L. Zhu, “Projector calibration from the camera image point of view,” Opt. Eng. 48, 117–208 (2009).
[CrossRef]

2006

T. Koninckx and L. Van Gool, “Real-time range acquisition by adaptive structured light,” IEEE Trans. Pattern Anal. Machine Intell. 28, 432–445 (2006).
[CrossRef]

2005

J. Pages, J. Salvi, C. Collewet, and J. Forest, “Optimised De Bruijn patterns for one-shot shape acquisition,” Image Vis. Comput. 23, 707–720 (2005).
[CrossRef]

2004

F. Blais, “Review of 20 years of range sensor development,” J. Electron. Imaging 13, 231–243 (2004).
[CrossRef]

J. Salvi, J. Pages, and J. Battle, “Pattern codification strategies in structured light systems,” Pattern Recogn. 37, 827–849 (2004).
[CrossRef]

2000

F. Chen, G. Brown, and M. Song, “Overview of three-dimensional shape measurement using optical methods,” Opt. Eng. 39, 10–22 (2000).
[CrossRef]

1998

D. Caspi, N. Kiryati, and J. Shamir, “Range imaging with adaptive color structured light,” IEEE Trans. Pattern Anal. Machine Intell. 20, 470–480 (1998).
[CrossRef]

J. Salvi, J. Batlle, and E. Mouaddib, “A robust-coded pattern projection for dynamic 3D scene measurement,” Pattern Recogn. Lett. 19, 1055–1065 (1998).
[CrossRef]

R. Morano, C. Ozturk, R. Conn, S. Dubin, S. Zietz, and J. Nissanov, “Structured light using pseudorandom codes,” IEEE Trans. Pattern Anal. Machine Intell. 322–327 (1998).
[CrossRef]

1997

C. Chen, Y. Hung, C. Chiang, and J. Wu, “Range data acquisition using color structured lighting and stereo vision,” Image Vis. Comput. 15, 445–456 (1997).
[CrossRef]

1991

A. Cumani, “Edge detection in multispectral images,” CVGIP: Graph. Models Image Process. 53, 40–51 (1991).
[CrossRef]

1989

H. Hügli and G. Maitre, “Generation and use of color pseudorandom sequences for coding structured light in active ranging,” Proc. SPIE 1010, 75–82 (1989).

1987

K. Boyer and A. Kak, “Color-encoded structured light for rapid active ranging,” IEEE Trans. Pattern Anal. Machine Intell. PAMI-9, 14–28 (1987).
[CrossRef]

1976

F. MacWilliams and N. Sloane, “Pseudo-random sequences and arrays,” Proc. IEEE 64, 1715–1729 (1976).
[CrossRef]

Albitar, I.

I. Albitar, P. Graebling, and C. Doignon, “Robust structured light coding for 3D reconstruction,” in Proceedings of the IEEE 11th International Conference on Computer Vision (IEEE, 2007), pp. 1–6.
[CrossRef]

Batlle, J.

J. Salvi, J. Batlle, and E. Mouaddib, “A robust-coded pattern projection for dynamic 3D scene measurement,” Pattern Recogn. Lett. 19, 1055–1065 (1998).
[CrossRef]

Battle, J.

J. Salvi, J. Pages, and J. Battle, “Pattern codification strategies in structured light systems,” Pattern Recogn. 37, 827–849 (2004).
[CrossRef]

Blais, F.

F. Blais, “Review of 20 years of range sensor development,” J. Electron. Imaging 13, 231–243 (2004).
[CrossRef]

Boyer, K.

K. Boyer and A. Kak, “Color-encoded structured light for rapid active ranging,” IEEE Trans. Pattern Anal. Machine Intell. PAMI-9, 14–28 (1987).
[CrossRef]

Brown, G.

F. Chen, G. Brown, and M. Song, “Overview of three-dimensional shape measurement using optical methods,” Opt. Eng. 39, 10–22 (2000).
[CrossRef]

Caspi, D.

D. Caspi, N. Kiryati, and J. Shamir, “Range imaging with adaptive color structured light,” IEEE Trans. Pattern Anal. Machine Intell. 20, 470–480 (1998).
[CrossRef]

Chen, C.

C. Chen, Y. Hung, C. Chiang, and J. Wu, “Range data acquisition using color structured lighting and stereo vision,” Image Vis. Comput. 15, 445–456 (1997).
[CrossRef]

Chen, F.

F. Chen, G. Brown, and M. Song, “Overview of three-dimensional shape measurement using optical methods,” Opt. Eng. 39, 10–22 (2000).
[CrossRef]

Chen, S.

S. Chen, Y. Li, and J. Zhang, “Vision processing for realtime 3-D data acquisition based on coded structured light,” IEEE Trans. Image Process. 17, 167–176 (2007).
[CrossRef]

Chiang, C.

C. Chen, Y. Hung, C. Chiang, and J. Wu, “Range data acquisition using color structured lighting and stereo vision,” Image Vis. Comput. 15, 445–456 (1997).
[CrossRef]

Collewet, C.

J. Pages, J. Salvi, C. Collewet, and J. Forest, “Optimised De Bruijn patterns for one-shot shape acquisition,” Image Vis. Comput. 23, 707–720 (2005).
[CrossRef]

Conn, R.

R. Morano, C. Ozturk, R. Conn, S. Dubin, S. Zietz, and J. Nissanov, “Structured light using pseudorandom codes,” IEEE Trans. Pattern Anal. Machine Intell. 322–327 (1998).
[CrossRef]

Cumani, A.

A. Cumani, “Edge detection in multispectral images,” CVGIP: Graph. Models Image Process. 53, 40–51 (1991).
[CrossRef]

Curless, B.

B. Curless and M. Levoy, “Better optical triangulation through spacetime analysis,” in Proceedings of the IEEE International Conference on Computer Vision (IEEE, 1995), pp. 987–994.
[CrossRef]

L. Zhang, B. Curless, and S. Seitz, “Rapid shape acquisition using color structured light and multi-pass dynamic programming,” in Proceedings of the 1st IEEE International Symposium on 3D Data Processing, Visualization, and Transmission (IEEE, 2002), pp. 24–36.
[CrossRef] [PubMed]

Doignon, C.

I. Albitar, P. Graebling, and C. Doignon, “Robust structured light coding for 3D reconstruction,” in Proceedings of the IEEE 11th International Conference on Computer Vision (IEEE, 2007), pp. 1–6.
[CrossRef]

Dubin, S.

R. Morano, C. Ozturk, R. Conn, S. Dubin, S. Zietz, and J. Nissanov, “Structured light using pseudorandom codes,” IEEE Trans. Pattern Anal. Machine Intell. 322–327 (1998).
[CrossRef]

Eisert, P.

P. Fechteler and P. Eisert, “Adaptive color classification for structured light systems,” in Proceedings of the 15th International Conference on Computer Vision and Pattern Recognition—Workshop on 3D Face Processing (IEEE, 2008), pp. 1–7.

Fechteler, P.

P. Fechteler and P. Eisert, “Adaptive color classification for structured light systems,” in Proceedings of the 15th International Conference on Computer Vision and Pattern Recognition—Workshop on 3D Face Processing (IEEE, 2008), pp. 1–7.

Fernandez, S.

J. Salvi, S. Fernandez, T. Pribanic, and X. Llado, “A state of the art in structured light patterns for surface profilometry,” Pattern Recogn. 43, 2666–2680 (2010).
[CrossRef]

Forest, J.

J. Pages, J. Salvi, C. Collewet, and J. Forest, “Optimised De Bruijn patterns for one-shot shape acquisition,” Image Vis. Comput. 23, 707–720 (2005).
[CrossRef]

Furukawa, R.

H. Kawasaki, R. Furukawa, R. Sagawa, and Y. Yagi, “Dynamic scene shape reconstruction using a single structured light pattern,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (IEEE, 2008), pp. 1–8.

Geys, I.

T. Koninckx, I. Geys, T. Jaeggli, L. Van Gool, and B. Leuven, “A graph cut based adaptive structured light approach for real-time range acquisition,” in Proceedings of the International Symposium on 3D Data Processing, Visualization and Transmission (IEEE Computer Society, 2004), pp. 413–421.
[CrossRef]

Graebling, P.

I. Albitar, P. Graebling, and C. Doignon, “Robust structured light coding for 3D reconstruction,” in Proceedings of the IEEE 11th International Conference on Computer Vision (IEEE, 2007), pp. 1–6.
[CrossRef]

Hall-Holt, O.

O. Hall-Holt and S. Rusinkiewicz, “Stripe boundary codes for real-time structured-light range scanning of moving objects,” in Proceedings of the Eighth IEEE International Conference on Computer Vision (IEEE, 2001), pp. 359–366.
[CrossRef]

Hügli, H.

H. Hügli and G. Maitre, “Generation and use of color pseudorandom sequences for coding structured light in active ranging,” Proc. SPIE 1010, 75–82 (1989).

Hung, Y.

C. Chen, Y. Hung, C. Chiang, and J. Wu, “Range data acquisition using color structured lighting and stereo vision,” Image Vis. Comput. 15, 445–456 (1997).
[CrossRef]

Jaeggli, T.

T. Koninckx, I. Geys, T. Jaeggli, L. Van Gool, and B. Leuven, “A graph cut based adaptive structured light approach for real-time range acquisition,” in Proceedings of the International Symposium on 3D Data Processing, Visualization and Transmission (IEEE Computer Society, 2004), pp. 413–421.
[CrossRef]

Je, C.

C. Je, S. W. Lee, and R.-H. Park, “High-contrast color-stripe pattern for rapid structured-light range imaging,” in Proceedings of the 8th European Conference on Computer Vision (Springer, 2004), pp. 95–107.

Kak, A.

K. Boyer and A. Kak, “Color-encoded structured light for rapid active ranging,” IEEE Trans. Pattern Anal. Machine Intell. PAMI-9, 14–28 (1987).
[CrossRef]

Kawasaki, H.

H. Kawasaki, R. Furukawa, R. Sagawa, and Y. Yagi, “Dynamic scene shape reconstruction using a single structured light pattern,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (IEEE, 2008), pp. 1–8.

Kiryati, N.

D. Caspi, N. Kiryati, and J. Shamir, “Range imaging with adaptive color structured light,” IEEE Trans. Pattern Anal. Machine Intell. 20, 470–480 (1998).
[CrossRef]

Koninckx, T.

T. Koninckx and L. Van Gool, “Real-time range acquisition by adaptive structured light,” IEEE Trans. Pattern Anal. Machine Intell. 28, 432–445 (2006).
[CrossRef]

T. Koninckx, I. Geys, T. Jaeggli, L. Van Gool, and B. Leuven, “A graph cut based adaptive structured light approach for real-time range acquisition,” in Proceedings of the International Symposium on 3D Data Processing, Visualization and Transmission (IEEE Computer Society, 2004), pp. 413–421.
[CrossRef]

Lee, S. W.

C. Je, S. W. Lee, and R.-H. Park, “High-contrast color-stripe pattern for rapid structured-light range imaging,” in Proceedings of the 8th European Conference on Computer Vision (Springer, 2004), pp. 95–107.

Leuven, B.

T. Koninckx, I. Geys, T. Jaeggli, L. Van Gool, and B. Leuven, “A graph cut based adaptive structured light approach for real-time range acquisition,” in Proceedings of the International Symposium on 3D Data Processing, Visualization and Transmission (IEEE Computer Society, 2004), pp. 413–421.
[CrossRef]

Levoy, M.

B. Curless and M. Levoy, “Better optical triangulation through spacetime analysis,” in Proceedings of the IEEE International Conference on Computer Vision (IEEE, 1995), pp. 987–994.
[CrossRef]

Li, H.

H. Li, R. Straub, and H. Prautzsch, “Structured light based reconstruction under local spatial coherence assumption,” in Proceedings of the Third International Symposium on 3D Data Processing, Visualization, and Transmission (IEEE Computer Society, 2006), pp. 575–582.
[CrossRef] [PubMed]

Li, Y.

S. Chen, Y. Li, and J. Zhang, “Vision processing for realtime 3-D data acquisition based on coded structured light,” IEEE Trans. Image Process. 17, 167–176 (2007).
[CrossRef]

Llado, X.

J. Salvi, S. Fernandez, T. Pribanic, and X. Llado, “A state of the art in structured light patterns for surface profilometry,” Pattern Recogn. 43, 2666–2680 (2010).
[CrossRef]

MacWilliams, F.

F. MacWilliams and N. Sloane, “Pseudo-random sequences and arrays,” Proc. IEEE 64, 1715–1729 (1976).
[CrossRef]

Maitre, G.

H. Hügli and G. Maitre, “Generation and use of color pseudorandom sequences for coding structured light in active ranging,” Proc. SPIE 1010, 75–82 (1989).

Morano, R.

R. Morano, C. Ozturk, R. Conn, S. Dubin, S. Zietz, and J. Nissanov, “Structured light using pseudorandom codes,” IEEE Trans. Pattern Anal. Machine Intell. 322–327 (1998).
[CrossRef]

Mouaddib, E.

J. Salvi, J. Batlle, and E. Mouaddib, “A robust-coded pattern projection for dynamic 3D scene measurement,” Pattern Recogn. Lett. 19, 1055–1065 (1998).
[CrossRef]

Nissanov, J.

R. Morano, C. Ozturk, R. Conn, S. Dubin, S. Zietz, and J. Nissanov, “Structured light using pseudorandom codes,” IEEE Trans. Pattern Anal. Machine Intell. 322–327 (1998).
[CrossRef]

Ozturk, C.

R. Morano, C. Ozturk, R. Conn, S. Dubin, S. Zietz, and J. Nissanov, “Structured light using pseudorandom codes,” IEEE Trans. Pattern Anal. Machine Intell. 322–327 (1998).
[CrossRef]

Pages, J.

J. Pages, J. Salvi, C. Collewet, and J. Forest, “Optimised De Bruijn patterns for one-shot shape acquisition,” Image Vis. Comput. 23, 707–720 (2005).
[CrossRef]

J. Salvi, J. Pages, and J. Battle, “Pattern codification strategies in structured light systems,” Pattern Recogn. 37, 827–849 (2004).
[CrossRef]

Park, R.-H.

C. Je, S. W. Lee, and R.-H. Park, “High-contrast color-stripe pattern for rapid structured-light range imaging,” in Proceedings of the 8th European Conference on Computer Vision (Springer, 2004), pp. 95–107.

Prautzsch, H.

H. Li, R. Straub, and H. Prautzsch, “Structured light based reconstruction under local spatial coherence assumption,” in Proceedings of the Third International Symposium on 3D Data Processing, Visualization, and Transmission (IEEE Computer Society, 2006), pp. 575–582.
[CrossRef] [PubMed]

Pribanic, T.

J. Salvi, S. Fernandez, T. Pribanic, and X. Llado, “A state of the art in structured light patterns for surface profilometry,” Pattern Recogn. 43, 2666–2680 (2010).
[CrossRef]

Rusinkiewicz, S.

O. Hall-Holt and S. Rusinkiewicz, “Stripe boundary codes for real-time structured-light range scanning of moving objects,” in Proceedings of the Eighth IEEE International Conference on Computer Vision (IEEE, 2001), pp. 359–366.
[CrossRef]

Sagawa, R.

H. Kawasaki, R. Furukawa, R. Sagawa, and Y. Yagi, “Dynamic scene shape reconstruction using a single structured light pattern,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (IEEE, 2008), pp. 1–8.

Salvi, J.

J. Salvi, S. Fernandez, T. Pribanic, and X. Llado, “A state of the art in structured light patterns for surface profilometry,” Pattern Recogn. 43, 2666–2680 (2010).
[CrossRef]

J. Pages, J. Salvi, C. Collewet, and J. Forest, “Optimised De Bruijn patterns for one-shot shape acquisition,” Image Vis. Comput. 23, 707–720 (2005).
[CrossRef]

J. Salvi, J. Pages, and J. Battle, “Pattern codification strategies in structured light systems,” Pattern Recogn. 37, 827–849 (2004).
[CrossRef]

J. Salvi, J. Batlle, and E. Mouaddib, “A robust-coded pattern projection for dynamic 3D scene measurement,” Pattern Recogn. Lett. 19, 1055–1065 (1998).
[CrossRef]

Seitz, S.

L. Zhang, B. Curless, and S. Seitz, “Rapid shape acquisition using color structured light and multi-pass dynamic programming,” in Proceedings of the 1st IEEE International Symposium on 3D Data Processing, Visualization, and Transmission (IEEE, 2002), pp. 24–36.
[CrossRef] [PubMed]

Shamir, J.

D. Caspi, N. Kiryati, and J. Shamir, “Range imaging with adaptive color structured light,” IEEE Trans. Pattern Anal. Machine Intell. 20, 470–480 (1998).
[CrossRef]

Sloane, N.

F. MacWilliams and N. Sloane, “Pseudo-random sequences and arrays,” Proc. IEEE 64, 1715–1729 (1976).
[CrossRef]

Song, M.

F. Chen, G. Brown, and M. Song, “Overview of three-dimensional shape measurement using optical methods,” Opt. Eng. 39, 10–22 (2000).
[CrossRef]

Straub, R.

H. Li, R. Straub, and H. Prautzsch, “Structured light based reconstruction under local spatial coherence assumption,” in Proceedings of the Third International Symposium on 3D Data Processing, Visualization, and Transmission (IEEE Computer Society, 2006), pp. 575–582.
[CrossRef] [PubMed]

Van Gool, L.

T. Koninckx and L. Van Gool, “Real-time range acquisition by adaptive structured light,” IEEE Trans. Pattern Anal. Machine Intell. 28, 432–445 (2006).
[CrossRef]

T. Koninckx, I. Geys, T. Jaeggli, L. Van Gool, and B. Leuven, “A graph cut based adaptive structured light approach for real-time range acquisition,” in Proceedings of the International Symposium on 3D Data Processing, Visualization and Transmission (IEEE Computer Society, 2004), pp. 413–421.
[CrossRef]

Wu, J.

C. Chen, Y. Hung, C. Chiang, and J. Wu, “Range data acquisition using color structured lighting and stereo vision,” Image Vis. Comput. 15, 445–456 (1997).
[CrossRef]

Yagi, Y.

H. Kawasaki, R. Furukawa, R. Sagawa, and Y. Yagi, “Dynamic scene shape reconstruction using a single structured light pattern,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (IEEE, 2008), pp. 1–8.

Zhang, J.

S. Chen, Y. Li, and J. Zhang, “Vision processing for realtime 3-D data acquisition based on coded structured light,” IEEE Trans. Image Process. 17, 167–176 (2007).
[CrossRef]

Zhang, L.

L. Zhang, B. Curless, and S. Seitz, “Rapid shape acquisition using color structured light and multi-pass dynamic programming,” in Proceedings of the 1st IEEE International Symposium on 3D Data Processing, Visualization, and Transmission (IEEE, 2002), pp. 24–36.
[CrossRef] [PubMed]

Zhang, X.

X. Zhang and L. Zhu, “Determination of edge correspondence using color codes for one-shot shape acquisition,” Opt. Lasers Eng. 49, 97–103 (2010).
[CrossRef]

X. Zhang and L. Zhu, “Projector calibration from the camera image point of view,” Opt. Eng. 48, 117–208 (2009).
[CrossRef]

X. Zhang and L. Zhu, “Robust calibration of a color structured light system using color correction,” in Proceedings of the Intelligent Robotics and Applications Second International Conference, ICIRA 2009 (Springer, 2009), Vol.  5928, pp. 936–946.

Zhu, L.

X. Zhang and L. Zhu, “Determination of edge correspondence using color codes for one-shot shape acquisition,” Opt. Lasers Eng. 49, 97–103 (2010).
[CrossRef]

X. Zhang and L. Zhu, “Projector calibration from the camera image point of view,” Opt. Eng. 48, 117–208 (2009).
[CrossRef]

X. Zhang and L. Zhu, “Robust calibration of a color structured light system using color correction,” in Proceedings of the Intelligent Robotics and Applications Second International Conference, ICIRA 2009 (Springer, 2009), Vol.  5928, pp. 936–946.

Zietz, S.

R. Morano, C. Ozturk, R. Conn, S. Dubin, S. Zietz, and J. Nissanov, “Structured light using pseudorandom codes,” IEEE Trans. Pattern Anal. Machine Intell. 322–327 (1998).
[CrossRef]

CVGIP: Graph. Models Image Process.

A. Cumani, “Edge detection in multispectral images,” CVGIP: Graph. Models Image Process. 53, 40–51 (1991).
[CrossRef]

IEEE Trans. Pattern Anal. Machine Intell.

D. Caspi, N. Kiryati, and J. Shamir, “Range imaging with adaptive color structured light,” IEEE Trans. Pattern Anal. Machine Intell. 20, 470–480 (1998).
[CrossRef]

K. Boyer and A. Kak, “Color-encoded structured light for rapid active ranging,” IEEE Trans. Pattern Anal. Machine Intell. PAMI-9, 14–28 (1987).
[CrossRef]

R. Morano, C. Ozturk, R. Conn, S. Dubin, S. Zietz, and J. Nissanov, “Structured light using pseudorandom codes,” IEEE Trans. Pattern Anal. Machine Intell. 322–327 (1998).
[CrossRef]

T. Koninckx and L. Van Gool, “Real-time range acquisition by adaptive structured light,” IEEE Trans. Pattern Anal. Machine Intell. 28, 432–445 (2006).
[CrossRef]

Image Vis. Comput.

J. Pages, J. Salvi, C. Collewet, and J. Forest, “Optimised De Bruijn patterns for one-shot shape acquisition,” Image Vis. Comput. 23, 707–720 (2005).
[CrossRef]

C. Chen, Y. Hung, C. Chiang, and J. Wu, “Range data acquisition using color structured lighting and stereo vision,” Image Vis. Comput. 15, 445–456 (1997).
[CrossRef]

J. Electron. Imaging

F. Blais, “Review of 20 years of range sensor development,” J. Electron. Imaging 13, 231–243 (2004).
[CrossRef]

Opt. Eng.

F. Chen, G. Brown, and M. Song, “Overview of three-dimensional shape measurement using optical methods,” Opt. Eng. 39, 10–22 (2000).
[CrossRef]

X. Zhang and L. Zhu, “Projector calibration from the camera image point of view,” Opt. Eng. 48, 117–208 (2009).
[CrossRef]

Opt. Lasers Eng.

X. Zhang and L. Zhu, “Determination of edge correspondence using color codes for one-shot shape acquisition,” Opt. Lasers Eng. 49, 97–103 (2010).
[CrossRef]

Pattern Recogn.

J. Salvi, J. Pages, and J. Battle, “Pattern codification strategies in structured light systems,” Pattern Recogn. 37, 827–849 (2004).
[CrossRef]

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Figures (11)

Fig. 1
Fig. 1

Framework of structured light technique.

Fig. 2
Fig. 2

Example of the projected and obtained patterns in the structured light system.

Fig. 3
Fig. 3

(a) Portable structured light system and six subjects: (b) girl, (c) Marseilles, (d) box, (e) pig, (f) book & bottle, and (g) sundries.

Fig. 4
Fig. 4

Space–time mapping of a Gaussian illuminant [20].

Fig. 5
Fig. 5

Ground truth: (a) codes (b) surfaces (c) magnified surfaces.

Fig. 6
Fig. 6

Point clouds and surfaces of girl: (a) point cloud of different algorithms on the practical codes, (b) point cloud of different algorithms on the theoretical codes, the surfaces from the correct points in (a). The algorithms from left to right are CG in Eqs. (4, 5, 6), DP, and M-DP.

Fig. 7
Fig. 7

Point clouds and surfaces of Marseilles: (a) point cloud from CG in Eq. (4), (b) point cloud from CG in Eq. (5), (c) point cloud from CG in Eq. (6), (d) surface from the correct points in (a), (e) surface from correct points in (b), (f) surface from correct points in (c), (g) point cloud from DP, (h) point cloud from M-DP, and (i) surface from correct points in (h).

Fig. 8
Fig. 8

Point clouds and surfaces of box: (a) point cloud from CG in Eq. (4), (b) point cloud from CG in Eq. (5), (c) point cloud from CG in Eq. (6), (d) surface from the correct points in (a), (e) surface from the correct points in (b), (f) surface from the correct points in (c), (g) point cloud from DP, (h) point cloud from M-DP, and (i) surface from the correct points in (h).

Fig. 9
Fig. 9

Point clouds and surfaces of pig: (a) point cloud of different algorithms on the practical codes, (b) point cloud of different algorithms on the theoretical codes; the surfaces from the correct points in (a). The algorithms from left to right are CG in Eqs. (4, 5, 6), DP, and M-DP.

Fig. 10
Fig. 10

Point clouds and surfaces of book & bottle: (a) point cloud of different algorithms on the practical codes and (b) point cloud of different algorithms on the theoretical codes; the surfaces from the correct points in (a). The algorithms from left to right are CG in Eqs. (4, 5, 6), DP, and M-DP.

Fig. 11
Fig. 11

Point clouds and surfaces of sundries: (a) point cloud of different algorithms on the practical codes, (b) point cloud of different algorithms on the theoretical codes; the surfaces from the correct points in (a). The algorithms from left to right are CG in Eqs. (4, 5, 6), DP, and M-DP.

Tables (5)

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Table 1 Relationship between Factors and Code Situations

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Table 2 Hamming Distance for Three Kinds of Code

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Table 3 Accuracy of the Method for Identifying Codes (%)

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Table 4 Performance of Different Decoding Algorithms on Theoretical Codes (%)

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Table 5 Performance of Different Decoding Algorithms on Practical Codes (%)

Equations (8)

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q i = p i 1 XOR p i ,     q i Q .
min i j ( k = 1 n ( q i + k XOR q j + k ) ) > 0 , i , j .
cor = ( q i , e j ) , where     q i = e j , q i Q , e j E ,
COR edge = { ( q i + 1 , e j + 1 ) , ... , ( q i + n , e j + n ) } if     k = 1 n ( q i + k XOR e j + k ) = 0.
COR color = { ( q i + 1 , e j + 1 ) , ... , ( q i + n , e j + n ) } if     k = 0 n ( p i + k XOR c j + k ) = 0 ,
COR mixed = { ( q i + 1 , e j + 1 ) , ... , ( q i + n , e j + n ) } if     k = 1 n ( q i + k XOR e j + k ) = 0 , and k = 0 n ( p i + k XOR c j + k ) = 0.
Accuracy = The number of correct correspondences The number of total detected correspondences .
Recall = The number of correct correspondences The number of total correspondences in ground truth .

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