Skip to main content
SpringerLink
Log in
Book cover

Advances in Modelling, Animation and Rendering pp 215–237Cite as

An Isosurface Continuity Algorithm for Super Adaptive Resolution Data *

  • Conference paper

Abstract

We present the chain-gang algorithm for isosurface rendering of super adap tive resolution (SAR) volume data in order to minimize (1) the space needed for storage of both the data and the isosurface and (2) the time taken for computation. The chain gang algorithm is able to resolve discontinuities in SAR data sets. Unnecessary computation is avoided by skipping over large sets of volume data deemed uninteresting. Memory space is saved by leaving the uninteresting voxels out of our octree data structure used to traverse the volume data. Our isosurface generation algorithm extends the Marching Cubes Algorithm in order to handle inconsistencies that can arise between abutting cells that are separated by both one and two levels of resolution.

Keywords:

isosurface rendering, adaptive resolution visualization, marching cubes, uncertainty visualization, chain-gang

This is a preview of subscription content, log in via an institution.

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   169.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   219.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD   219.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Michael B. Cox and David Ellsworth. Application-controlled demand paging for out-of-core visualization. Proc. Of Proc ‘87. IEEE Computer Society Press, October 1997.

    Google Scholar 

  2. Michael B. Cox and David Ellsworth. Managing big data for scientific visualization. ACM Siggraph ‘87, 21, August 1997. Course #4 Exploring Gigabyte Datasets in Real-Time: Algorithms, Data Management, and Time-Critical Design.

    Google Scholar 

  3. Klaus Engel, Rudiger Westermann, and Thomas Ertl. Isosurface extraction techniques for web-based volume visualization. In Volume Visualization,Visualization 99, California, October 1999.

    Google Scholar 

  4. William Hibbard. Connecting people to computations and people to people.Computer Graphics,32(3):10–12,1998.

    Article  Google Scholar 

  5. William Hibbard. The visad java class library developers guide. The World Wide Web, November 1999. http://www.ssec.wisc.edulbillh/visad.html

    Google Scholar 

  6. Eric C. LaMar, Bernd Hamann, and Kenneth I. Joy. Multiresolution techniques for interactive texture-based volume visualization. In David Ebert, Markus Gross, and Bernd Hamann, editors, IEEE Visualization ‘89,pages 355–362, San Francisco, 1999. IEEE.

    Google Scholar 

  7. C. Charles Law, Kenneth M. Martin, William J. Schroeder, and Joshua Temkin. A multi-threaded streaming pipeline architecture for large structured data sets. In Volume Visualization,Volume Visualization 99, California, October 1999.

    Google Scholar 

  8. Yarden Livnat, Han-Wei Shen, and Christopher R. Johnson. A near optimal isosurface extraction algorithm for structured and unstructured grids. IEEE Transactions on Visual Computer Graphics,2(1):73–84,1996.

    Article  Google Scholar 

  9. William E. Lorensen and Harvey E. Cline. Marching cubes: a high resolution 3d surface construction algorithm. Comput Graph,21:163–169, 1987.

    Article  Google Scholar 

  10. Claudio Montani, Riccardo Scateni, and Roberto Scopigno. Discretized marching cubes. In R. Daniel Bergeron and Arie E. Kaufman, editors, Proceedings of the Conference on Visualization,pages 281–287, Los Alamitos, CA, USA, October 1994. IEEE Computer Society Press.

    Google Scholar 

  11. Alex T. Pang, Craig M. Wittenbrink, and Suresh K. Lodha. Approaches to uncertainty visualization. The Visual Computer,13(8):370–390, 1997. ISSN 01782789.

    Article  Google Scholar 

  12. William J. Schroeder, Kenneth M. Martin, and William E. Lorensen. The Visualization Toolkit. Prentice-Hall, Inc, Upper Saddle River, New Jersey 07458, 1996.

    Google Scholar 

  13. Raj Shekhar, Elias Fayyad, Roni Yagel, and J. Fredrick Cornhill. Octree-based decimation of marching cubes surfaces. In Roni Yagel and Gregory M. Nielson, editors, Pmceedings of the Conference on Visualization,pages 335–344, Los Alamitos, October 27—November 1 1996. IEEE.

    Google Scholar 

  14. Renben Shu, Chen Zhou, and Mohan S Kankanhalli. Adaptive marching cubes. The Visual Computer,11:202–217, 1995.

    Google Scholar 

  15. Gunther H. Weber, Oliver Kreylos, Terry J Ligocki, John M. Shalf, Hans Hagen, Bernd Hamann, and Kenneth I Joy. Extraction of crack-free isosurfaces from adaptive mesh refinement data. In D.S. Ebert, J.M. Favre, and R. Peikert, editors,Data Visualization 2001(Proceedings of VisSym 2001),pages 25–34, Vienna, Austria, 2001. Springer-Verlag.

    Google Scholar 

  16. Ruediger Westermann, Leif P. Kobbelt, and Thomas Ertl. Real-time exploration of regular volume data by adaptive reconstruction of isosurfaces. The Visual Computer, 15:100–111,1999.

    Article  Google Scholar 

  17. Jane Wilhelms and Allen Van Gelder. Topological ambiguities in isosurface generation. Technical report, University of California, Santa Cruz, California, December 1990. Extended abstract in ACM Computer Graphics. 2, 5 79–86.

    Article  Google Scholar 

  18. Jane Wilhelms and Allen Van Gelder. Octrees for faster isosurface generation. ACM Transactions on Graphics,11(3):201–227, July 1992.

    Article  MATH  Google Scholar 

  19. Pak Chung Wong and R. Daniel Bergeron. Multiresolution multidimensional wavelet brushing. In Roni Yagel and Gregory M. Nielson, editors, IEEE Visualization ‘86, pages 141–148. IEEE, 1996.

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Center for Virtual Reality and Visualization Donau-City-Strass, 1 A-1220, Vienna, Austria

    Robert S Laramee

  2. Department of Computer Science Kingsbury Hall, University of New Hampshire Durham, New Hampshire 03824, USA

    R. Daniel Bergeron

Authors
  1. Robert S Laramee
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. R. Daniel Bergeron
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. School of Media, Arts and Communication, Bournemouth University, Talbot Campus, Fern Barrow, Poole, BH12 5BB, UK

    John Vince PhD, FBCS, CEng

  2. Department of Electronic Imaging and Media Communications, University of Bradford, Bradford, BD7 1DP, UK

    Rae Earnshaw BSc, MSc, FBCS, CEng

Rights and permissions

Reprints and permissions

Copyright information

© 2002 Springer-Verlag London

About this paper

Cite this paper

Laramee, R.S., Bergeron, R.D. (2002). An Isosurface Continuity Algorithm for Super Adaptive Resolution Data *. In: Vince, J., Earnshaw, R. (eds) Advances in Modelling, Animation and Rendering. Springer, London. https://doi.org/10.1007/978-1-4471-0103-1_14

Download citation

  • DOI: https://doi.org/10.1007/978-1-4471-0103-1_14

  • Publisher Name: Springer, London

  • Print ISBN: 978-1-4471-1118-4

  • Online ISBN: 978-1-4471-0103-1

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics

Search

Navigation