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A Sampling Theorem for a 2D Surface

  • Conference paper
Scale Space and Variational Methods in Computer Vision (SSVM 2011)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 6667))

Abstract

The sampling rate for signal reconstruction has been and remains an important and central criterion in numerous applications. We propose, in this paper, a new approach to determining an optimal sampling rate for a 2D-surface reconstruction using the so-called Two-Thirds Power Law. This paper first introduces an algorithm of a 2D surface reconstruction from a 2D image of circular light patterns projected on the surface. Upon defining the Two-Thirds Power Law we show how the extracted spectral information helps define an optimal sampling rate of the surface, reflected in the number of projected circular patterns required for its reconstruction. This result is of interest in a number of applications such as 3D face recognition and development of new efficient 3D cameras. Substantive examples are provided.

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References

  1. Faugeras, O., Luong, Q.-T.: The Geometry of Multiple Images (2001)

    Google Scholar 

  2. Wei, Z., Zhou, F., Zhang, G.: 3D coordinates measurement based on structured light sensor. Sensors and Actuators A: Physical 120, 527–535 (2005)

    Article  Google Scholar 

  3. Asada, M., Ichikawa, H., Tsuji, S.: Determining of surface properties by projecting a stripe pattern. In: Proc. Int. Conf. on Pattern Recognition, pp. 1162–1164 (1986)

    Google Scholar 

  4. Dipanda, A., Woo, S.: Towards a real-time 3D shape reconstruction using a structured light system. Pattern Recognition 38, 1632–1650 (2005)

    Article  Google Scholar 

  5. Batlle, J., Mouaddib, E., Salvi, J.: Recent Progress in Coded Structured Light as a Technique to solve the Correspondence Problem: A Survey. Pattern Recognition 31, 963–982 (1998)

    Article  Google Scholar 

  6. Papoulis, A.: Signal Analysis. McGraw-Hill, New York (1977)

    MATH  Google Scholar 

  7. Eldar, Y.C.: Compressed Sensing of Analog Signals in Shift-Invariant Spaces. IEEE Transactions on Signal Processing 57(8) (August 2009)

    Google Scholar 

  8. Jerri, A.J.: The Shannon Sampling Theorem - Its Various Extensions and Applications: A Tutorial Review. Proceedings of The IEEE 65(11) (November 1977)

    Google Scholar 

  9. Maoz, U., Portugaly, E., Flash, T., Weiss, Y.: Noise and the two-thirds power law

    Google Scholar 

  10. de’ Sperati, C., Viviani, P.: The Relationship between Curvature and Velocity in Two-Dimensional Smooth Pursuit Eye Movements. The Journal of Neuroscience 17, 3932–3945 (1997)

    Google Scholar 

  11. Schaal, S., Sternad, D.: Origins and violations of the 2/3 power law in rhythmic 3D movements. Experimental. Brain Research,, 60–72 (2001)

    Google Scholar 

  12. Lee, D., Krim, H.: 3D surface reconstruction using structured circular light patterns. In: Blanc-Talon, J., Bone, D., Philips, W., Popescu, D., Scheunders, P. (eds.) ACIVS 2010, Part I. LNCS, vol. 6474, pp. 279–289. Springer, Heidelberg (2010)

    Chapter  Google Scholar 

  13. Lacquaniti, F., Terzuolo, C., Viviani, P.: The law relating the kinematic and figural aspects of drawing movements. Acta Psychologica, 115–130 (1983)

    Google Scholar 

  14. Pollefeys, M., Koch, R., Van Gool, L.: Self-Calibration and Metric Reconstruction Inspite of Varying and Known Intrinsic Camera Parameters. International Journal of Computer Vision, 7–25 (1999)

    Google Scholar 

  15. Armangue, X., Salvi, J., Batlle, J.: A Comparative Review Of Camera Calibrating Methods with Accuracy Evaluation. Pattern Recognition 35, 1617–1635 (2000)

    MATH  Google Scholar 

  16. Sturm, P.: On Focal Length Calibration from Two Views. In: IEEE International Conference on Computer Vision and Pattern Recognition, pp. 145–150 (2001)

    Google Scholar 

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Lee, D., Krim, H. (2012). A Sampling Theorem for a 2D Surface. In: Bruckstein, A.M., ter Haar Romeny, B.M., Bronstein, A.M., Bronstein, M.M. (eds) Scale Space and Variational Methods in Computer Vision. SSVM 2011. Lecture Notes in Computer Science, vol 6667. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-24785-9_47

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  • DOI: https://doi.org/10.1007/978-3-642-24785-9_47

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-24784-2

  • Online ISBN: 978-3-642-24785-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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