Journal of Visualization

, Volume 19, Issue 4, pp 715–726 | Cite as

On-the-fly simplification of large iso-surfaces with per-cube vertex modifiability detection

  • Tao HouEmail author
  • Li Chen
Regular Paper


Marching Cubes based iso-surface extraction is widely used for data visualization. However, the increasing size of volume sets has made extracted iso-surfaces difficult to manipulate, and applying out-of-core simplification on them is considerably slow. We present an on-the-fly simplification algorithm for out-of-core iso-surfaces generated by Marching Cubes based extraction. Our algorithm shifts between extraction and decimation during the processing of volume sets, and never stores the entire extracted iso-surface in the main memory. The key of our algorithm is that we exploit the extraction pattern of Marching Cubes to determine when the mesh operator can be applied on certain generated vertices. This enables the decimation to be applied after any specified number of triangles are extracted. It also provides a framework for on-the-fly processing of large iso-surfaces. Our algorithm is more efficient than cascading out-of-core extraction and simplification, while providing high simplification quality comparable to in-core algorithms.

Graphical abstract


Iso-surface simplification On-the-fly processing  Out-of-core processing Volumeset visualization 



This work was supported in part by the National Natural Science Foundation of China (61272225, 61572274, 91515103, 51261120376). We would like to thank the Stanford Computer Graphics Laboratory for the bunny dataset, web site for the foot and teapot datasets, and Michael Garland for providing the QSlim implementation.


  1. Akio D, Koide A (1991) An efficient method of triangulating equi-valued surfaces by using tetrahedral cells. IEICE Trans Inf Syst 74(1):214–224Google Scholar
  2. Attali D, Cohen-Steiner D, Edelsbrunner H (2005) Extraction and simplification of iso-surfaces in tandem. In: Eurographics symposium on geometry processing 2005, The Eurographics Association, pp 139–148Google Scholar
  3. Bernardini F, Rushmeier H, Martin IM, Mittleman J, Taubin G (2002) Building a digital model of michelangelo’s florentine pieta. Comput Gr Appl IEEE 22(1):59–67CrossRefGoogle Scholar
  4. Brodsky D, Pedersen JB, (2003) A parallel framework for simplification of massive meshes. In: Parallel and large-data visualization and graphics (2003) PVG 2003. IEEE symposium on, IEEE, pp 17–24Google Scholar
  5. Cignoni P, Rocchini C, Scopigno R (1998) Metro: measuring error on simplified surfaces. Comput Gr Forum, Wiley Online Libr 17:167–174CrossRefGoogle Scholar
  6. Cignoni P, Montani C, Rocchini C, Scopigno R (2003) External memory management and simplification of huge meshes. Vis Comput Gr IEEE Trans 9(4):525–537CrossRefGoogle Scholar
  7. Garland M, Heckbert PS (1997) Surface simplification using quadric error metrics. In: Proceedings of the 24th annual conference on computer graphics and interactive techniques, ACM Press/Addison-Wesley Publishing Co., pp 209–216Google Scholar
  8. Hoppe H (1996) Progressive meshes. In: Proceedings of the 23rd annual conference on computer graphics and interactive techniques, ACM, pp 99–108Google Scholar
  9. Isenburg M, Lindstrom P (2005) Streaming meshes. In: Visualization (2005) VIS 05. IEEE, IEEE, pp 231–238Google Scholar
  10. Isenburg M, Lindstrom P, Gumhold S, Snoeyink J (2003) Large mesh simplification using processing sequences. In: Proceedings of the 14th IEEE visualization 2003 (VIS’03), IEEE computer society, p 61Google Scholar
  11. Ju T, Losasso F, Schaefer S, Warren J (2002) Dual contouring of hermite data. In: ACM Transactions on Graphics (TOG) - Proceedings of ACM SIGGRAPH 2002, ACM, NY, USA, vol 21, pp 339–346Google Scholar
  12. Lindstrom P (2000) Out-of-core simplification of large polygonal models. In: Proceedings of the 27th annual conference on computer graphics and interactive techniques, ACM Press/Addison-Wesley Publishing Co., pp 259–262Google Scholar
  13. Lindstrom P, Silva CT (2001) A memory insensitive technique for large model simplification. In: Proceedings of the conference on visualization’01, IEEE computer society, pp 121–126Google Scholar
  14. Lorensen WE, Cline HE (1987) Marching cubes: a high resolution 3D surface construction algorithm. ACM Siggr Comput Gr ACM 21:163–169CrossRefGoogle Scholar
  15. Manson J, Schaefer S (2010) Isosurfaces over simplicial partitions of multiresolution grids. Comput Gr Forum, Wiley Online Libr 29:377–385CrossRefGoogle Scholar
  16. Newman TS, Yi H (2006) A survey of the marching cubes algorithm. Comput Gr 30(5):854–879CrossRefGoogle Scholar
  17. Nielson GM, Hamann B (1991) The asymptotic decider: resolving the ambiguity in marching cubes. In: Proceedings of the 2nd conference on visualization’91, IEEE Computer Society Press, pp 83–91Google Scholar
  18. Peng Y, Chen L, Yong JH (2014) Importance-driven isosurface decimation for visualization of large simulation data based on openCL. Comput Sci Eng 16(1):24–32CrossRefGoogle Scholar
  19. Prince C (2000) Progressive meshes for large models of arbitrary topology. Master’s thesis, University of WashingtonGoogle Scholar
  20. Rossignac J, Borrel P (1993) Multi-resolution 3D approximations for rendering complex scenes. Springer, BerlinGoogle Scholar
  21. Schaefer S, Warren J (2005) Dual marching cubes: primal contouring of dual grids. Comput Gr Forum, Wiley Online Libr 24:195–201CrossRefGoogle Scholar
  22. Schroeder WJ, Zarge JA, Lorensen WE (1992) Decimation of triangle meshes. ACM Siggr Comput Gr ACM 26:65–70CrossRefGoogle Scholar
  23. Shirley P, Tuchman A (1990) A polygonal approximation to direct scalar volume rendering. In: Proceedings of the 1990 Workshop on Volume Visualization, ACM, NY, USA, vol 24, pp 63–70.
  24. Van Gelder A, Wilhelms J (1994) Topological considerations in isosurface generation. ACM Trans Gr (TOG) 13(4):337–375CrossRefGoogle Scholar
  25. Wu J, Kobbelt L (2003) A stream algorithm for the decimation of massive meshes. Gr Interface 3:185–192Google Scholar

Copyright information

© The Visualization Society of Japan 2016

Authors and Affiliations

  1. 1.School of SoftwareTsinghua UniversityBeijingChina
  2. 2.VMware Information Technology (China) Co. LtdBeijingChina

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