Advertisement

Meshless Parameterization for Dimensional Reduction Integrated in 3D Voxel Reconstruction Using a Single PC

  • Yunli Lee
  • Dongwuk Kyoung
  • Keechul Jung
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4872)

Abstract

Shape-From-Silhouettes (SFS) is one of the most popular ideas for reconstructing the 3D voxel of an object from silhouettes images. This paper presents a method based SFS and pre-computing methods for 3D voxel reconstruction using a single PC. This method is reduced the memory usage. Towards this approach, a meshless parameterization for dimensional reduction is integrated in the process to obtain object representation in 2D form. Since the meshless parameterization requires the solution of large linear system on a whole 3D voxel, by taking the advantages of 3D voxel reconstruction process, the meshless parameterization is computed locally. The proposed method is able to implement an optimize system and utilize in various applications.

Keywords

Meshless parameterization dimensional reduction 3D voxel reconstruction shape from silhouettes single PC 

References

  1. 1.
    Matsuyama, T., Wu, X., Takai, T., Wada, T.: Real-Time Dynamic 3D Object Shape Reconstruction and High-Fidelity Texture Mapping for 3D Video. IEEE Transactions on Circuits and Systems for Technology 14(3), 357–369 (2004)CrossRefGoogle Scholar
  2. 2.
    Kong, G., Kanade, T., Bouguet, J., Holler, M.: A Real Time System for Robust 3D Voxel Reconstruction of Human Motion. In: Proceedings IEEE Conference on Computer Vision and Pattern Recognition, Hilton Head Island, SC, USA, vol. 2, pp. 714–720 (2000)Google Scholar
  3. 3.
    Van der Maaten, L.J.P., Postma, E.O., Van den Herik, H.J.: Dimensionality Reduction: A Comparative Review (2007) Google Scholar
  4. 4.
    Floater, M.S.: Meshless Parameterization and B-spline Surface Approximation. In: Cipolla, R., Martin, R. (eds.) The Mathematics of Surfaces IX, pp. 1–18. Springer, Heidelberg (2000)Google Scholar
  5. 5.
    Floater, M.S., Reimers, M.: Meshless Parameterization and Surface Reconstruction. Computer Aided Geometric Design, 77–92 (2001)Google Scholar
  6. 6.
    Floater, M.S., Hormann, K.: Surface Parameterization: a Tutorial and Survey. Advances in Multiresolution for Geometric Modelling, 157–186 (2004)Google Scholar
  7. 7.
    Lee, Y., Kyoung, D., Han, E., Jung, K.: Dimension Reduction in 3D Gesture Recognition Using Meshless Parameterization. In: Chang, L.-W., Lie, W.-N., Chiang, R. (eds.) PSIVT 2006. LNCS, vol. 4319, pp. 64–73. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  8. 8.
    Voledine, T., Roose, D., Van der straeten, D: Efficient Triangulation of Point Clouds using Floater Parameterization, Report TW385 (2004) Google Scholar
  9. 9.
    Jain, R., Kasturi, R., Schunck, B.G.: Machine Vision. McGraw-Hill, Inc., New York (1995)Google Scholar
  10. 10.
    Jolliffe, I.: Principal component analysis. Technical report, Springer (October 2002) Google Scholar
  11. 11.
    Kruskal, J.B., Wish, M.: Multidimensional Scaling, Ch. 1, 3, 5, pp. 7–19, 48, 73. Sage Publications Inc., Newbury Park, CA (1978) Google Scholar
  12. 12.
    Kyoung, D., Lee, Y., Beak, W., Han, E., Yang, J., Jung, K.: Efficient 3D Voxel Reconstruction using Precomputing Method for Gesture Recognition. In: First Korea Japan Joint Workshop on Pattern Recognition (2006) Google Scholar
  13. 13.

Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Yunli Lee
    • 1
  • Dongwuk Kyoung
    • 1
  • Keechul Jung
    • 1
  1. 1.School of Media, College of Information Technology, Soongsil University, SeoulSouth Korea

Personalised recommendations