Skip to main content
SpringerLink
Log in
Book cover

International Symposium on Visual Computing

ISVC 2009: Advances in Visual Computing pp 847–856Cite as

An Adaptive Cutaway with Volume Context Preservation

  • Conference paper

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 5876))

Abstract

Knowledge expressiveness of scientific data is one of the most important visualization goals. However, current volume visualization systems require a lot of expertise from the final user. In this paper, we present a GPU-based ray casting interactive framework that computes two initial complementary camera locations and allows to select the focus interactively, on interesting structures keeping the volume’s context information with an adaptive cutaway technique. The adaptive cutaway surrounds the focused structure while preserving a depth immersive impression in the data set. Finally, we present a new brush widget to edit interactively the opening of the cutaway and to graduate the context in the final image.

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   129.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   169.99
Price excludes VAT (USA)
  • Compact, lightweight 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. Viola, I., Kanitsar, A., Gröller, E.: Importance-driven feature enhancement in volume visualization. IEEE Trans. on Visualization and CG 11, 408–418 (2005)

    Article  Google Scholar 

  2. Bruckner, S., Gröller, E.: Volumeshop: An interactive system for direct volume illustration. In: IEEE Visualization 2005, pp. 671–678 (2005)

    Google Scholar 

  3. Rautek, P., Bruckner, S., Gröller, M.E., Viola, I.: Illustrative visualization: New technology or useless tautology? SIGGRAPH Comput. Graph. 42 (2008)

    Google Scholar 

  4. Krüger, J., Schneider, J., Westermann, R.: Clearview: An interactive context preserving hotspot visualization technique. In: IEEE Trans. on Visualization and Computer Graphics (Proc. Visualization / Information Visualization 2006), vol. 12 (2006)

    Google Scholar 

  5. Patel, D., Giertsen, C., Thurmond, J., Gröller, M.: Illustrative rendering of seismic data. In: Lensch, H., Bodo Rosenhahn, H.S. (eds.) Proceeding of Vision Modeling and Visualization, pp. 13–22 (2007)

    Google Scholar 

  6. Burns, M., Finkelstein, A.: Adaptive cutaways for comprehensible rendering of polygonal scenes. ACM Trans. Graph. 27, 1–7 (2008)

    Article  Google Scholar 

  7. Wang, S., Kaufman, A.: Volume sculpting. In: ACM Symp. Interactive 3D Graphics, pp. 151–156 (1995)

    Google Scholar 

  8. Konrad-Verse, O., Preim, B., Littmann, A.: Virtual resection with a deformable cutting plane. In: Proc. of Simulation und Visualisierung, pp. 203–214 (2004)

    Google Scholar 

  9. Correa, C., Silver, D., Chen, M.: Feature aligned volume manipulation for illustration and visualization. IEEE Transactions on Visualization and Computer Graphics 12, 1069–1076 (2006)

    Article  Google Scholar 

  10. Bruckner, S., Gröller, M.E.: Exploded views for volume data. IEEE Trans. on Visualization and Computer Graphics 12, 1077–1084 (2006)

    Article  Google Scholar 

  11. Zhou, J., Hinz, M., Tonnies, K.: Focal region-guided feature-based volume rendering. In: Symp. on 3D Data Processing Visualization and Transmission, p. 87 (2002)

    Google Scholar 

  12. Bordoloi, U., Shen, H.: View selection for volume rendering. IEEE Visualization, 62 (2005)

    Google Scholar 

  13. Takahashi, S., Fujishiro, I., Takeshima, Y., Nishita, T.: A feature-driven approach to locating optimal viewpoints for volume visualization. vis. 0, 63 (2005)

    Google Scholar 

  14. Viola, I., Feixas, M., Sbert, M., Gröller, E.: Importance-driven focus of attention. IEEE Trans. on Visualization and Computer Graphics 12, 933–940 (2006)

    Article  Google Scholar 

  15. Mühler, K., Neugebauer, M., Tietjen, C., Preim, B.: Viewpoint selection for intervention planning. In: IEEE Symp. on Visualization 2007, pp. 267–274 (2007)

    Google Scholar 

  16. Vázquez, P.P., I Navazo, E.M.: Representative views and paths for volume models. In: Smart Graphics, pp. 106–117 (2008)

    Google Scholar 

  17. Kohlmann, P., Bruckner, S., Kanitsar, A., Gröller, E.: The livesync++: Enhancements of an interaction metaphor. Graphics Interface (08), 81–88

    Google Scholar 

  18. Polonsky, O., Patane, G., Biasotti, S., Gotsman, C., Spagnuolo, M.: What’s in an image? The Visual Computer 21, 840–847 (2005)

    Article  Google Scholar 

  19. Strengert, M., Kraus, M., Ertl, T.: Pyramid methods in gpu-based image processing. In: VMV 2006, pp. 169–176 (2006)

    Google Scholar 

  20. Gorski, K., Hivon, E., Banday, A., Wandelt, B., Hansen, F., Reinecke, M., Bartelman, M.: Healpix – a framework for high resolution discretization, and fast analysis of data distributed on the sphere. The Astrophysical Journal 622, 759 (2005)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Polytechnic University of Catalonia, Spain

    S. Grau

  2. University of Barcelona, Spain

    A. Puig

Authors
  1. S. Grau
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. A. Puig
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Department of Computer Science and Engineering, University of Nevada, Reno, USA

    George Bebis

  2. NASA Ames Research Center, Moffett Field, CA, USA

    Richard Boyle

  3. Lawrence Berkeley National Laboratory, Berkeley, CA, USA

    Bahram Parvin

  4. Desert Research Institute, Reno, NV, USA

    Darko Koracin

  5. Graduate School of Science and Engineering, Saitama University, 255 Shimo-Okubo, Sakura-ku, Saitama-shi, 338-8570, 338-8570, Japan

    Yoshinori Kuno

  6. Microsoft Research, Redmond, WA, USA

    Junxian Wang

  7. Univ. of Zurich, Department of Informatics, Winterthurerstr. 190, P.O. Box, 8057, Zurich, Switzerland

    Renato Pajarola

  8. Lawrence Livermore National Laboratory, 94550, Livermore, CA, USA

    Peter Lindstrom

  9. University of Applied Sciences Bonn-Rhein-Sieg, 53754, Sankt Augustin, Germany

    André Hinkenjann

  10.  ,  

    Miguel L. Encarnação

  11. SCI Institute & School of Computing, University of Utah, 84112, Salt Lake City, UT, USA

    Cláudio T. Silva

  12. Desert Research Institute, 89512, Reno, NV, USA

    Daniel Coming

Rights and permissions

Reprints and permissions

Copyright information

© 2009 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Grau, S., Puig, A. (2009). An Adaptive Cutaway with Volume Context Preservation. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2009. Lecture Notes in Computer Science, vol 5876. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-10520-3_81

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-10520-3_81

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-10519-7

  • Online ISBN: 978-3-642-10520-3

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation