Abstract

This article presents a fast and accurate method to measure human faces for medical applications. To encode an object point, several random patterns are projected. A correlation technique, which takes only the area of one pixel into account, is used to locate the homologous points. It could be shown that band limited random patterns are helpful for noise reduction. The comparison of the point cloud of a measured plane with an ideal one showed a standard deviation less then 50μm. Furthermore a depth difference of 20μm is detectable.

© 2006 Optical Society of America

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References

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  1. Y. Ma, S. Soatto and J. Kosecka, An Invitation to 3-D Vision (Springer, 2003)
  2. R. I. Hartley, "In Defense of the Eight-Point Algorithm," inIEEE Transactions on Pattern Analysis and Machine Intelligence, Vol.  19, No. 6, pp. 580-593, (1997)
  3. O. Faugeras, Three-Dimensional Computer Vision (Artificial Intelligence) (MIT Press, 1993)
  4. F. Devernay, O. Bantiche and E. Coste-Manire, "Structured light on dynamic scenes using standard stereoscopy algorithms," in Rapport de recherche de l’INRIA, No. 4477, (June 2002), http://www.inria.fr/rrrt/rr-4477.html
  5. P. Albrecht and B. Michaelis, "Stereo Photogrammetry with Improved Spatial Resolution," in 14th International Conference on Pattern Recognition, pp. 845-849, (1998)
  6. I. E. Abdou and K. Y. Wong, "Analysis of Linear Interpolation Schemes for Bi-Level Image Applications" in IBM Journal of Research and Development, Vol. 26, No. 6, pp. 667-680, (1982)

1997

R. I. Hartley, "In Defense of the Eight-Point Algorithm," inIEEE Transactions on Pattern Analysis and Machine Intelligence, Vol.  19, No. 6, pp. 580-593, (1997)

Hartley, R. I.

R. I. Hartley, "In Defense of the Eight-Point Algorithm," inIEEE Transactions on Pattern Analysis and Machine Intelligence, Vol.  19, No. 6, pp. 580-593, (1997)

IEEE Transactions on Pattern Analysis and Machine Intelligence

R. I. Hartley, "In Defense of the Eight-Point Algorithm," inIEEE Transactions on Pattern Analysis and Machine Intelligence, Vol.  19, No. 6, pp. 580-593, (1997)

Other

O. Faugeras, Three-Dimensional Computer Vision (Artificial Intelligence) (MIT Press, 1993)

F. Devernay, O. Bantiche and E. Coste-Manire, "Structured light on dynamic scenes using standard stereoscopy algorithms," in Rapport de recherche de l’INRIA, No. 4477, (June 2002), http://www.inria.fr/rrrt/rr-4477.html

P. Albrecht and B. Michaelis, "Stereo Photogrammetry with Improved Spatial Resolution," in 14th International Conference on Pattern Recognition, pp. 845-849, (1998)

I. E. Abdou and K. Y. Wong, "Analysis of Linear Interpolation Schemes for Bi-Level Image Applications" in IBM Journal of Research and Development, Vol. 26, No. 6, pp. 667-680, (1982)

Y. Ma, S. Soatto and J. Kosecka, An Invitation to 3-D Vision (Springer, 2003)

Supplementary Material (1)

» Media 1: GIF (1792 KB)     

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Figures (7)

Fig. 1.
Fig. 1.

Schematic arrangement of the measuring setup

Fig. 2.
Fig. 2.

Bilinear subpixel correlation function

Fig. 3.
Fig. 3.

Bicubic subpixel correlation function

Fig. 4.
Fig. 4.

Example parts (75 × 100 pixels) of a binary pattern, one pattern with limited maximum frequency and a bandlimited one

Fig. 5.
Fig. 5.

Evaluation of the step height sensitivity using a plane with milled grooves between 5μm and 160μm, the projected patterns correspond to the ones shown in Fig. 4

Fig. 6.
Fig. 6.

Deviation from a flat reference in mm

Fig. 7.
Fig. 7.

(1.7MB) GIF animation of a rendered point cloud of a human face. The picture shows in addition a detailed view of the eye’s region as a pointcloud and as a rendered image.

Equations (1)

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ρ = i = 1 N ( l i l ̅ ) * ( r i r ̅ ) i = 1 N ( l i l ̅ ) 2 * i = 1 N ( r i r ̅ ) 2

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