Advertisement

Journal of Computer Science and Technology

, Volume 19, Issue 5, pp 596–606 | Cite as

Geometric signal compression

  • Kun ZhouEmail author
  • Hu-Jun Bao
  • Jiao-Ying Shi
  • Qun-Sheng Peng
Article

Abstract

Compression of mesh attributes becomes a challenging problem due to the great need for efficient storage and fast transmission. This paper presents a novel geometric signal compression framework for all mesh attributes, including position coordinates, normal, color, texture, etc. Within this framework, mesh attributes are regarded as geometric signals defined on mesh surfaces. A planar parameterization algorithm is first proposed to map 3D meshes to 2D parametric meshes. Geometric signals are then transformed into 2D signals, which are sampled into 2D regular signals using an adaptive sampling method. The JPEG2000 standard for still image compression is employed to effectively encode these regular signals into compact bit-streams with high rate/distortion ratios. Experimental results demonstrate the great application potentials of this framework.

Keywords

mesh geometry compression parameterization JPEG2000 wavelet transform 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. [1]
    Taubin G, Rossignac J. 3D geometry compression. InACM SIGGRAPH Conference Course Notes 21, 1999–2000.Google Scholar
  2. [2]
    Alliez P, Desbrun M. Valence-driven connectivity encoding of 3D meshes. InProc. EUROGRAPHICS'01, 2001.Google Scholar
  3. [3]
    Bajaj C, Pascucci V, Zhuang G, Single resolution compression of arbitrary triangular meshes with properties. InData Compression Conference Proceedings, 1999, pp.247–256.Google Scholar
  4. [4]
    Deering M. Geometry compression. InProc. SIGGRAPH'95, 1995, pp.13–20.Google Scholar
  5. [5]
    Gumhold S, Strasser W. Real time compression of triangle mesh connectivity. InProc. SIGGRAPH'98, 1998, pp.133–140.Google Scholar
  6. [6]
    Li J, Kuo C C. A dual graph approach to 3D triangular mesh compression. InProc. the IEEE International Conference on Image Processing, 1998.Google Scholar
  7. [7]
    Rossignac J. EdgeBreaker: Connectivity compression for triangler meshes.IEEE Transactions on Visualization and Computer Graphics, 1999, pp.47–61.Google Scholar
  8. [8]
    Taubin G, Rossignac J. Geometric compression through topological surgery.ACM Transactions on Graphics, 1998, 17(2): 84–115.CrossRefGoogle Scholar
  9. [9]
    Touma C, Gotsman C. Triangle mesh compression. InProc. Graphics Interface'98 1998, pp:26–34.Google Scholar
  10. [10]
    Alliez P, Desbrun M. Progressive compression for lossless transmission of triangle meshes. InProc. SIGGRAPH'01, 2001, pp.195–202.Google Scholar
  11. [11]
    Bajaj C, Pascucci V, Zhuang G. Progressive compression and transmission of arbitrary triangular meshes. InProc. IEEE Visualization'99, 1999, pp.307–316.Google Scholar
  12. [12]
    Cohen-Or D, Levin D, Remez O. Progressive compression of arbitrary triangular meshes. InProc. IEEE Visualization'99, 1999, pp.67–72.Google Scholar
  13. [13]
    Hoppe H. Progressive meshes. InProc. SIGGRAPH'96, 1996, pp.99–108.Google Scholar
  14. [14]
    Taubin G, Guéziec A, Hom W, Lazarus F. Progressive forest split compression. InProc. SIGGRAPH'98, 1998, pp.123–132.Google Scholar
  15. [15]
    Kobbelt L, Taubin G. Geometric Signal Processing on Large Polyhedral Meshes. Course Notes 17, InSIGGRAPH 2001 Conference, 2001.Google Scholar
  16. [16]
    Sweldens W, Schröder P. Digital Geometric Signal Processing. Course Notes 50, InSIGGRAPH 2001 Conference, 2001.Google Scholar
  17. [17]
    Taubin G. A signal processing approach to fair surface design. InProc. SIGGRAPH'95, 1995, pp.351–358.Google Scholar
  18. [18]
    Karni Z, Gotsman C. Spectral compression of mesh geometry. InProc. SIGGRAPH'00, 2000, pp.279–286.Google Scholar
  19. [19]
    Khodakovsky A, Schröder P, Sweldens W. Progressive geometry compression. InProc. SIGGRAPH'00, 2000, pp.271–278.Google Scholar
  20. [20]
    Gu X, Gortler S J, Hoppe H. Geometry images. InProc. of SIGGRAPH'02, 2002, pp.355–361.Google Scholar
  21. [21]
    Eck M, DeRose T, Duchamp T, Hoppe H, Lounsbery M, Stuetzle W. Multiresolution analysis of arbitrary meshes. InProc. SIGGRAPH'95, 1995, pp.173–182.Google Scholar
  22. [22]
    Floater M S. Parameterization and smooth approximation.Computer Aided Geometric Design, 1997, 14: 231–250.zbMATHCrossRefMathSciNetGoogle Scholar
  23. [23]
    Sander P V, Snyder J, Gortler S J, Hoppe H. Texture mapping progressive meshes. InProc. SIGGRAPH'2001, 2001, pp.409–416.Google Scholar
  24. [24]
    Lindstrom P, Turk G. Fast and memory efficient polygonal simplification. InProc. IEEE Visualization'98, October 1998, pp.279–286.Google Scholar
  25. [25]
    Lee A, Sweldens W, Schröder P, Cowsar L, Dobkin D. MAPS: Multiresolution adaptive parameterization of surfaces. InProc SIGGRAPH'98, 1998, pp.95–104.Google Scholar
  26. [26]
    Cignoni P, Rocchini C, Scopigno R. Metro: Measuring error on simplified surfaces.Computer Graphics Forum, 1998, 17(2): 167–174.CrossRefGoogle Scholar
  27. [27]
    ISO/IEC JTC1/SC29/WG1 N1577: JPEG2000 Part II Working Draft Version 1.0 Pre-Release A, Jan. 26, 2000.Google Scholar
  28. [28]
    Turk G. Texture synthesis on surfaces. InProc. SIGGRAPH'2001, 2001, pp.347–354.Google Scholar

Copyright information

© Science Press, Beijing China and Allerton Press Inc., Beijing China and Allerton Press Inc. 2004

Authors and Affiliations

  • Kun Zhou
    • 1
    Email author
  • Hu-Jun Bao
    • 1
  • Jiao-Ying Shi
    • 1
  • Qun-Sheng Peng
    • 1
  1. 1.State Key Lab of CAD & CGZhejiang UniversityHangzhouP.R. China

Personalised recommendations