“Opacity optimization for 3D line fields” by Günther, Roessl and Theisel

  • ©Tobias Günther, Christian Roessl, and Holger Theisel




    Opacity optimization for 3D line fields


Session Title: Artistic Rendering & Stylization



    For the visualization of dense line fields, the careful selection of lines to be rendered is a vital aspect. In this paper, we present a global line selection approach that is based on an optimization process. Starting with an initial set of lines that covers the domain, all lines are rendered with a varying opacity, which is subject to the minimization of a bounded-variable least-squares problem. The optimization strives to keep a balance between information presentation and occlusion avoidance. This way, we obtain view-dependent opacities of the line segments, allowing a real-time free navigation while minimizing the danger of missing important structures in the visualization. We compare our technique with existing local and greedy approaches and apply it to data sets in flow visualization, medical imaging, physics, and computer graphics.


    1. Annen, T., Theisel, H., Rössl, C., Ziegler, G., and Seidel, H.-P. 2008. Vector field contours. In Proc. Graphics Interface, 97–105. Google ScholarDigital Library
    2. Candelaresi, S., and Brandenburg, A. 2011. Decay of helical and nonhelical magnetic knots. Phys. Rev. E 84, 016406.Google ScholarCross Ref
    3. Chen, Y., Cohen, J., and Krolik, J. 2007. Similarity-guided streamline placement with error evaluation. IEEE Transactions on Visualization and Computer Graphics 13, 1448–1455. Google ScholarDigital Library
    4. Coleman, T. F., and Li, Y. 1996. A reflective newton method for minimizing a quadratic function subject to bounds on some of the variables. SIAM J. on Optimization 6, 4, 1040–1058. Google ScholarDigital Library
    5. Eichelbaum, S., Hlawitschka, M., and Scheuermann, G. 2013. LineAO — improved three-dimensional line rendering. IEEE Transactions on Visualization and Computer Graphics 19, 3, 433–445. Google ScholarDigital Library
    6. Everts, M. H., Bekker, H., Roerdink, J. B. T. M., and Isenberg, T. 2009. Depth-dependent halos: Illustrative rendering of dense line data. IEEE Transactions on Visualization and Computer Graphics 15, 1299–1306. Google ScholarDigital Library
    7. Frederich, O., Wassen, E., and Thiele, F. 2008. Prediction of the flow around a short wall-mounted cylinder using LES and DES. Journal of Numerical Analysis, Industrial and Applied Mathematics (JNAIAM) 3, 3-4, 231–247.Google Scholar
    8. Furuya, S., and Itoh, T. 2008. A streamline selection technique for integrated scalar and vector visualization. In IEEE Visualization Poster Session.Google Scholar
    9. Günther, T., Bürger, K., Westermann, R., and Theisel, H. 2011. A view-dependent and inter-frame coherent visualization of integral lines using screen contribution. Proc. Vision, Modeling, and Visualization (VMV), 215–222.Google Scholar
    10. Jobard, B., and Lefer, W. 1997. Creating evenly-spaced streamlines of arbitrary density. Proc. Eurographics Workshop on Visualization in Scientific Computing 7, 45–55.Google Scholar
    11. Jobard, B., and Lefer, W. 2001. Multiresolution flow visualization. WSCG 2001 Conference Proceedings, 33–37.Google Scholar
    12. Kutz, B. M., Kowarsch, U., Kessler, M., and Krämer, E. 2012. Numerical investigation of helicopter rotors in ground effect. In 30th AIAA Applied Aerodynamics Conference.Google Scholar
    13. Lee, T.-Y., Mishchenko, O., Shen, H.-W., and Crawfis, R. 2011. View point evaluation and streamline filtering for flow visualization. In Proc. IEEE Pacific Visualization, 83–90. Google ScholarDigital Library
    14. Li, L., and Shen, H.-W. 2007. Image-based streamline generation and rendering. IEEE Transactions on Visualization and Computer Graphics 13, 630–640. Google ScholarDigital Library
    15. Li, L., Hsien, H. H., and Shen, H. W. 2008. Illustrative streamline placement and visualization. IEEE Pacific Visualization Symposium 2008, 79–86.Google Scholar
    16. Liu, Z., Moorhead, R., and Groner, J. 2006. An advanced evenly-spaced streamline placement algorithm. IEEE Transactions on Visualization and Computer Graphics 12, 965–972. Google ScholarDigital Library
    17. Luft, T., Colditz, C., and Deussen, O. 2006. Image enhancement by unsharp masking the depth buffer. ACM Trans. Graph. 25, 3, 1206–1213. Google ScholarDigital Library
    18. Ma, J., Wang, C., and Shene, C.-K. 2013. Coherent view-dependent streamline selection for importance-driven flow visualization. Proc. SPIE 8654, Visualization and Data Analysis.Google Scholar
    19. Marchesin, S., Chen, C.-K., Ho, C., and Ma, K.-L. 2010. View-dependent streamlines for 3D vector fields. IEEE Transactions on Visualization and Computer Graphics 16, 1578–1586. Google ScholarDigital Library
    20. Mattausch, O., Theussl, T., Hauser, H., and Gröller, E. 2003. Strategies for interactive exploration of 3D flow using evenly-spaced illuminated streamlines. In Proc. Spring Conference on Computer Graphics (SSCG), ACM, 213–222. Google ScholarDigital Library
    21. Maule, M., Comba, J. L., Torchelsen, R. P., and Bastos, R. 2011. A survey of raster-based transparency techniques. Computers & Graphics 35, 6, 1023–1034. Google ScholarDigital Library
    22. McLoughlin, T., Jones, M., Laramee, R., Malki, R., Masters, I., and Hansen, C. 2012. Similarity measures for enhancing interactive streamline seeding. IEEE Transactions on Visualization and Computer Graphics. Google ScholarDigital Library
    23. Mebarki, A., Alliez, P., and Devillers, O. 2005. Farthest point seeding for efficient placement of streamlines. In IEEE Visualization, 479–486.Google Scholar
    24. Tao, J., Ma, J., Wang, C., and Shene, C. 2013. A unified approach to streamline selection and viewpoint selection for 3D flow visualization. IEEE Transactions on Visualization and Computer Graphics 19, 393–406. Google ScholarDigital Library
    25. Turk, G., and Banks, D. 1996. Image-guided streamline placement. In Proc. SIGGRAPH, 453–460. Google ScholarDigital Library
    26. Verma, V., Kao, D., and Pang, A. 2000. A flow-guided streamline seeding strategy. In IEEE Visualization, 163–170. Google ScholarDigital Library
    27. Wang, C., and Shen, H.-W. 2011. Information theory in scientific visualization. Entropy 13, 1, 254–273.Google ScholarCross Ref
    28. Xu, L., Lee, T.-Y., and Shen, H.-W. 2010. An information-theoretic framework for flow visualization. In IEEE Transactions on Visualization and Computer Graphics, 1216–1224. Google ScholarDigital Library
    29. Yang, J. C., Hensley, J., Grün, H., and Thibieroz, N. 2010. Real-time concurrent linked list construction on the GPU. Computer Graphics Forum 29, 4, 1297–1304. Google ScholarDigital Library
    30. Ye, X., Kao, D., and Pang, A. 2005. Strategy for seeding 3D streamlines. IEEE Visualization Conference, 471–478.Google Scholar
    31. Yu, Y., Tung, C., van der Wall, B., Pausder, H.-J., Burley, C., Brooks, T., Beaumier, P., Mercker, Y. D. E., and Pengel, K. 2002. The HART-II test: Rotor wakes and aeroacoustics with higher-harmonic pitch control (HHC) inputs — the joint German/French/Dutch/US project. American Helicopter Society 58th Annual Forum.Google Scholar
    32. Yu, H., Wang, C., Shene, C.-K., and Chen, J. 2012. Hierarchical streamline bundles. IEEE Transactions on Visualization and Computer Graphics 18, 8, 1353–1367. Google ScholarDigital Library
    33. Zöckler, M., Stalling, D., and Hege, H.-C. 1996. Interactive visualization of 3D vector fields using illuminated stream lines. In IEEE Visualization, 107–113. Google ScholarDigital Library

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