Advertisement

The Visual Computer

, Volume 34, Issue 6–8, pp 817–827 | Cite as

An image-based method for animated stroke rendering

  • Tamás UmenhofferEmail author
  • László Szirmay-Kalos
  • László Szécsi
  • Zoltán Lengyel
  • Gábor Marinov
Original Article

Abstract

This paper presents an image-space stroke rendering algorithm that provides temporally coherent placement of lines at particles that are moving with object surfaces. We generate particles in image space and move them according to an image-space velocity field. Consistent image-space density is achieved by a deterministic rejection-based algorithm that uses low-discrepancy series to filter out overpopulated areas and to fill in underpopulated regions. Our line stabilization method can solve the temporal continuity problems of image-space techniques. The multi-pass algorithm is implemented entirely on the GPU using geometry shaders and vertex transform feedback. Our method provides high-quality results and is implemented as an interactive post processing step. We also provide a wide toolset for artists to control the final rendering style and extended the method to process real-life RGBZ footage.

Keywords

NPR Stroke rendering Hatching 

Notes

Funding

This study was funded by the Hungarian Scientific Research Fund (OTKA K–124124).

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

Supplementary material

Supplementary material 1 (mp4 202446 KB)

References

  1. 1.
    Bénard, P., Bousseau, A., Thollot, J.: Dynamic solid textures for real-time coherent stylization. In: Proceedings of the 2009 Symposium on Interactive 3D Graphics and Games, I3D ’09, pp. 121–127 (2009)Google Scholar
  2. 2.
    Bénard, P., Bousseau, A., Thollot, J.: State-of-the-art report on temporal coherence for stylized animations. Comput. Graph. Forum 30(8), 2367–2386 (2011)CrossRefGoogle Scholar
  3. 3.
    Bénard, P., Cole, F., Kass, M., Mordatch, I., Hegarty, J., Senn, M.S., Fleischer, K., Pesare, D., Breeden, K.: Stylizing animation by example. ACM Trans. Graph. 32(4), 119:1–119:12 (2013)CrossRefzbMATHGoogle Scholar
  4. 4.
    Bénard, P., Lagae, A., Vangorp, P., Lefebvre, S., Drettakis, G., Thollot, J.: A dynamic noise primitive for coherent stylization. Comp. Graph. Forum 29(4), 1497–1506 (2010)CrossRefGoogle Scholar
  5. 5.
    Bousseau, A., Neyret, F., Thollot, J., Salesin, D.: Video watercolorization using bidirectional texture advection. ACM Trans. Graph. 26(3), 104 (2007)CrossRefGoogle Scholar
  6. 6.
    Breslav, S., Szerszen, K., Markosian, L., Barla, P., Thollot, J.: Dynamic 2D patterns for shading 3D scenes. In: Proceedings of SIGGRAPH 2007 (2007)Google Scholar
  7. 7.
    Cornish, D., Rowan, A., Luebke, D.: View-dependent particles for interactive non-photorealistic rendering. In: Proceedings of the Graphics Interface, pp. 151–158 (2001)Google Scholar
  8. 8.
    Cunzi, M., Thollot, J., Paris, S., Debunne, G., Gascuel, J.D., Durand, F.: Dynamic canvas for immersive non-photorealistic walkthroughs. In: Proceedings of Graphics Interface (2003)Google Scholar
  9. 9.
    Elber, G.: Interactive line art rendering of freeform surfaces. Comput. Graph. Forum 18(3), 1–12 (1999)CrossRefGoogle Scholar
  10. 10.
    Farnebäck, G.: Two-frame motion estimation based on polynomial expansion. In: Proceedings of the 13th Scandinavian Conference on Image Analysis, SCIA’03, pp. 363–370 (2003)Google Scholar
  11. 11.
    Fišer, J., Jamriška, O., Lukáč, M., Shechtman, E., Asente, P., Lu, J., Sýkora, D.: StyLit: illumination-guided example-based stylization of 3D renderings. ACM Trans. Graph. 35(4), 92 (2016)Google Scholar
  12. 12.
    Girshick, A., Interrante, V., Haker, S., Lemoine, T.: Line direction matters: an argument for the use of principal directions in 3d line drawings. In: Proceedings of the 1st International Symposium on Non-photorealistic Animation and Rendering, pp. 43–52 (2000)Google Scholar
  13. 13.
    Hertzmann, A., Jacobs, C.E., Oliver, N., Curless, B., Salesin, D.H.: Image analogies. In: Proceedings of SIGGRAPH ’01, pp. 327–340 (2001)Google Scholar
  14. 14.
    Hertzmann, A., Zorin, D.: Illustrating smooth surfaces. Proc. SIGGRAPH 2000, 517–526 (2000)Google Scholar
  15. 15.
    Kalnins, R.D., Markosian, L., Meier, B.J., Kowalski, M.A., Lee, J.C., Davidson, P.L., Webb, M., Hughes, J.F., Finkelstein, A.: WYSIWYG NPR: drawing strokes directly on 3D models. ACM Trans. Graph. 21(3), 755–762 (2002)CrossRefGoogle Scholar
  16. 16.
    Kaplan, M., Gooch, B., Cohen, E.: Interactive artistic rendering. In: Proceedings of the 1st International Symposium on Non-photorealistic Animation and Rendering, pp. 67–74 (2000)Google Scholar
  17. 17.
    Kass, M., Pesare, D.: Coherent noise for non-photorealistic rendering. In: Proceedings of SIGGRAPH 2011, pp. 30:1–30:6 (2011)Google Scholar
  18. 18.
    Kim, Y., Yu, J., Yu, X., Lee, S.: Line-art illustration of dynamic and specular surfaces. ACM Trans. Graph. 27(5), 156 (2008)CrossRefGoogle Scholar
  19. 19.
    Klein, A.W., Li, W., Kazhdan, M.M., Corrêa, W.T., Finkelstein, A., Funkhouser, T.A.: Non-photorealistic virtual environments. In: Proceedings of SIGGRAPH ’00, pp. 527–534 (2000)Google Scholar
  20. 20.
    Kowalski, M.A., Markosian, L., Northrup, J., Bourdev, L.D., Barzel, R., Holden, L.S., Hughes, J.F.: Art-based rendering of fur, grass, and trees. Proc. SIGGRAPH 99, 433–438 (1999)Google Scholar
  21. 21.
    Lake, A., Marshall, C., Harris, M., Blackstein, M.: Stylized rendering techniques for scalable real-time 3d animation. In: Proceedings of the 1st International Symposium on Non-photorealistic Animation and Rendering, pp. 13–20 (2000)Google Scholar
  22. 22.
    Lee, H., Kwon, S., Lee, S.: Real-time pencil rendering. In: International Symposium on Non-Photorealistic Animation and Rendering, pp. 37–45 (2006)Google Scholar
  23. 23.
    Lu, J., Sander, P.V., Finkelstein, A.: Interactive painterly stylization of images, videos and 3D animations. In: Proceedings of I3D 2010 (2010)Google Scholar
  24. 24.
    Meier, B.J.: Painterly rendering for animation. In: Proceedings of SIGGRAPH ’96, pp. 477–484 (1996)Google Scholar
  25. 25.
    Niederreiter, H.: Random Number Generation and Quasi-Monte Carlo Methods. Society for Industrial and Applied Mathematics, Philadelphia (1992)CrossRefzbMATHGoogle Scholar
  26. 26.
    Praun, E., Hoppe, H., Webb, M., Finkelstein, A.: Real-time hatching. Proceedings of SIGGRAPH 2001, 579–584 (2001)Google Scholar
  27. 27.
    Salisbury, M.P., Anderson, S.E., Barzel, R., Salesin, D.H.: Interactive pen and ink illustration. In: Proceedings of SIGGRAPH ’94, pp. 101–108 (1994)Google Scholar
  28. 28.
    Singh, M., Schaefer, S.: Suggestive hatching. In: Proceedings of Computational Aesthetics’10, pp. 25–32 (2010)Google Scholar
  29. 29.
    Szirmay-Kalos, L.: Filtering and gradient estimation for distance fields by quadratic regression. Period. Polytech. Electr. Eng. Comput. Sci. 59(4), 175–180 (2015)CrossRefGoogle Scholar
  30. 30.
    Umenhoffer, T., Szécsi, L., Szirmay-Kalos, L.: Hatching for motion picture production. Comput. Graph. Forum 30(2), 533–542 (2011)CrossRefGoogle Scholar
  31. 31.
    Vanderhaeghe, D., Barla, P., Thollot, J., Sillion, F.: Dynamic point distribution for stroke-based rendering. In: Proceedings of the Eurographics Symposium on Rendering, pp. 139–146 (2007)Google Scholar
  32. 32.
    Vergne, R., Pacanowski, R., Barla, P., Granier, X., Schlick, C.: Light warping for enhanced surface depiction. ACM Trans. Graph. 28(3), 25 (2009)CrossRefGoogle Scholar
  33. 33.
    Suarez, J., Belhadj, F., Boyer, V.: Real-time 3D rendering with hatching. Vis. Comput. 33(10), 1319–1334 (2017)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Department of Control Engineering and Information TechnologyBudapest University of Technology and EconomicsBudapestHungary
  2. 2.Limes Superior Ltd.BudapestHungary

Personalised recommendations