The Visual Computer

, Volume 31, Issue 4, pp 455–469 | Cite as

Multi-resolution terrain rendering with GPU tessellation

  • HyeongYeop Kang
  • Hanyoung Jang
  • Chang-Sik Cho
  • JungHyun Han
Original Article

Abstract

GPU tessellation is very efficient and is reshaping the terrain-rendering paradigm. We present a novel terrain-rendering algorithm based on GPU tessellation. The planar domain of the terrain is partitioned into a set of tiles, and a coarse-grained quadtree is constructed for each tile using a screen-space error metric. Then, each node of the quadtree is input to the GPU pipeline together with its own tessellation factors. The nodes are tessellated and the vertices of the tessellated mesh are displaced by filtering the displacement maps. The multi-resolution scheme is designed to optimize the use of GPU tessellation. Further, it accepts not only height maps but also geometry images, which displace more vertices toward the higher curvature feature parts of the terrain surface such that the surface detail can be well reconstructed with a small number of vertices. The efficiency of the proposed method is proven through experiments on large terrain models. When the screen-space error threshold is set to a pixel, a terrain surface tessellated into 8.5 M triangles is rendered at 110 fps on commodity PCs.

Keywords

Terrain rendering GPU tessellation  Height map Geometry image 

Notes

Acknowledgments

This research is supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MEST) (NRF-2012R1A2A2A06047007). It is also supported by Ministry of Culture, Sports and Tourism (MCST) and Korea Creative Content Agency (KOCCA) in the Culture Technology (CT) Research and Development Program 2013.

Supplementary material

371_2014_941_MOESM1_ESM.m1v (26.6 mb)
ESM 1 (M1V 27,243 kb)

References

  1. 1.
  2. 2.
    Berry, J.: Unlock dems to identify upland ridges. GEOWorld 22(5), 14–15 (2009)Google Scholar
  3. 3.
  4. 4.
    Cignoni, P., Ganovelli, F., Gobbetti, E., Marton, F., Ponchio, F., Scopigno, R.: Bdam batched dynamic adaptive meshes for high performance terrain visualization. Comput. Graph. Forum 22(3), 505–514 (2003). doi: 10.1111/1467-8659.00698
  5. 5.
    Cignoni, P., Ganovelli, F., Gobbetti, E., Marton, F., Ponchio, F., Scopigno, R.: Planet-sized batched dynamic adaptive meshes (p-bdam). In: Proceedings of the 14th IEEE Visualization 2003 (VIS’03), pp. 147–154. IEEE Computer Society, Washington, DC, USA (2003). doi: 10.1109/VISUAL.2003.1250366
  6. 6.
    Cignoni, P., Puppo, E., Scopigno, R.: Representation and visualization of terrain surfaces at variable resolution. Visual Comput. 13(5), 199–217 (1997). doi: 10.1007/s003710050099
  7. 7.
    Dachsbacher, C., Stamminger, M.: Rendering procedural terrain by geometry image warping. In: Proceedings of the Fifteenth Eurographics conference on Rendering Techniques, pp. 103–110. Eurographics Association, Aire-la-Ville, Switzerland (2004). doi: 10.2312/EGWR/EGSR04/103-110
  8. 8.
    Duchaineau, M., Wolinsky, M., Sigeti, D.E., Miller, M.C., Aldrich, C., Mineev-Weinstein, M.B.: Roaming terrain: real-time optimally adapting meshes. In: Proceedings of the 8th conference on Visualization ’97, pp. 81–88. IEEE Computer Society Press, Los Alamitos (1997). http://dl.acm.org/citation.cfm?id=266989.267028
  9. 9.
    El-Sana, J., Varshney, A.: Generalized view-dependent simplification. Comput. Graph. Forum 18(3), 83–94 (1999). doi: 10.1111/1467-8659.00330 CrossRefGoogle Scholar
  10. 10.
    Evans, W., Kirkpatrick, D., Townsend, G.: Right-triangulated irregular networks. Algorithmica 30(2), 264–286 (2001). doi: 10.1007/s00453-001-0006-x CrossRefMATHMathSciNetGoogle Scholar
  11. 11.
    Feng, W.W., Kim, B.U., Yu, Y., Peng, L., Hart, J.: Feature-preserving triangular geometry images for level-of-detail representation of static and skinned meshes. ACM Trans. Graph. 29(2), 11:1–11:13 (2010). doi: 10.1145/1731047.1731049
  12. 12.
    Gu, X., Gortler, S.J., Hoppe, H.: Geometry images. ACM Trans. Graph. 21(3), 355–361 (2002). doi: 10.1145/566654.566589 CrossRefGoogle Scholar
  13. 13.
    Hoppe, H.: View-dependent refinement of progressive meshes. In: Proceedings of the 24th annual conference on Computer graphics and interactive techniques, pp. 189–198. ACM Press/Addison-Wesley Publishing Co., New York (1997). doi: 10.1145/258734.258843
  14. 14.
    Hoppe, H.: Smooth view-dependent level-of-detail control and its application to terrain rendering. In: Proceedings of the conference on Visualization ’98, pp. 35–42. IEEE Computer Society Press, Los Alamitos (1998). http://dl.acm.org/citation.cfm?id=288216.288221
  15. 15.
    Hwa, L.M., Duchaineau, M.A., Joy, K.I.: Adaptive 4–8 texture hierarchies. In: Proceedings of the conference on Visualization ’04, pp. 219–226. IEEE Computer Society, Washington, DC (2004). doi: 10.1109/VISUAL.2004.4
  16. 16.
    Jang, H., Han, J.: Feature-preserving displacement mapping with graphics processing unit (GPU) tessellation. Comp. Graph. Forum 31(6), 1880–1894 (201). doi: 10.1111/j.1467-8659.2012.03068.x CrossRefGoogle Scholar
  17. 17.
    Lindstrom, P., Koller, D., Ribarsky, W., Hodges, L.F., Faust, N., Turner, G.A.: Real-time, continuous level of detail rendering of height fields. In: Proceedings of the 23rd annual conference on Computer graphics and interactive techniques, pp. 109–118. ACM, New York (1996) doi:10.1145/237170.237217. http://doi.acm.org/10.1145/237170.237217
  18. 18.
    Lindstrom, P., Pascucci, V.: Visualization of large terrains made easy. In: Proceedings of the conference on Visualization ’01, pp. 363–371. IEEE Computer Society, Washington, DC (2001). http://dl.acm.org/citation.cfm?id=601671.601729
  19. 19.
    Lindstrom, P., Pascucci, V.: Terrain simplification simplified: a general framework for view-dependent out-of-core visualization. IEEE Trans. Vis. Comput. Graph. 8(3), 239–254 (2002). doi: 10.1109/TVCG.2002.1021577 CrossRefGoogle Scholar
  20. 20.
    Livny, Y., Kogan, Z., El-Sana, J.: Seamless patches for gpu-based terrain rendering. Vis. Comput. 25(3), 197–208 (2009). doi: 10.1007/s00371-008-0214-3 CrossRefGoogle Scholar
  21. 21.
    Livny, Y., Sokolovsky, N., Grinshpoun, T., El-Sana, J.: A GPU persistent grid mapping for terrain rendering. Vis. Comput. 24(2), 139–153 (2008). doi: 10.1007/s00371-007-0180-1 CrossRefGoogle Scholar
  22. 22.
    Losasso, F., Hoppe, H.: Geometry clipmaps: terrain rendering using nested regular grids. ACM Trans. Graph. 23(3), 769–776 (2004). doi: 10.1145/1015706.1015799 CrossRefGoogle Scholar
  23. 23.
    Pajarola, R.: Large scale terrain visualization using the restricted quadtree triangulation. In: Proceedings of the conference on Visualization ’98, pp. 19–26. IEEE Computer Society Press, Los Alamitos (1998). http://dl.acm.org/citation.cfm?id=288216.288219
  24. 24.
    Pajarola, R., Gobbetti, E.: Survey of semi-regular multiresolution models for interactive terrain rendering. Vis. Comput. 23(8), 583–605 (2007). doi: 10.1007/s00371-007-0163-2 CrossRefGoogle Scholar
  25. 25.
    Puppo, E.: Variable resolution terrain surfaces. In: Proceedings of the 8th Canadian Conference on Computational Geometry, pp. 202–210. Carleton University Press (1996). http://dl.acm.org/citation.cfm?id=648249.751895
  26. 26.
    Ripolles, O., Ramos, F., Puig-Centelles, A., Chover, M.: Real-time tessellation of terrain on graphics hardware. Comput. Geosci. 41, 147–155 (2012). doi: 10.1016/j.cageo.2011.08.025 CrossRefGoogle Scholar
  27. 27.
    Samet, H.: Applications of spatial data structures: Computer graphics, image processing, and GIS. Addison-Wesley Longman Publishing Co., Inc, Boston (1990)Google Scholar
  28. 28.
    Schneider, J., Westermann, R.: GPU-friendly high-quality terrain rendering. WSCG 14, 49–56 (2006)Google Scholar
  29. 29.
    Sullivan, J.M.: Curvature measures for discrete surfaces. In: ACM SIGGRAPH 2005 Courses. ACM, New York (2005). doi: 10.1145/1198555.1198662
  30. 30.
    Tatarchuk, N.: Dynamic terrain rendering on gpus using real-time tessellation. In: Engel W. (ed.) ShaderX 7: Advanced Rendering Techniques. Charles River Media (2009)Google Scholar
  31. 31.
    Valdetaro, A., Nunes, G., Raposo, A., Feijo, B., Toledo, R.d.: Lod terrain rendering by local parallel processing on gpu. In: Proceedings of the 2010 Brazilian Symposium on Games and Digital Entertainment, pp. 182–188. IEEE Computer Society, Washington, DC (2010). doi: 10.1109/SBGAMES.2010.30
  32. 32.
    Wagner, D.: Terrain geomorphing in the vertex shader. In: ShaderX2: Shader Programming Tips and Tricks with DirectX 9.0, pp. 18–32. Wordware Publishing, Inc., Texas (2003)Google Scholar
  33. 33.
    Xia, J., El-Sana, J., Varshney, A.: Adaptive real-time level-of-detail based rendering for polygonal models. IEEE Trans. Vis. Comput. Graph. 3(2), 171–183 (1997). doi: 10.1109/2945.597799 CrossRefGoogle Scholar
  34. 34.
    Yoon, S.E., Gobbetti, E., Kasik, D., Manocha, D.: Real-Time Massive Model Rendering. Morgan and Claypool Publishers, San Rafael (2008)Google Scholar
  35. 35.
    Yoshizawa, S., Belyaev, A., Seidel, H.P.: A fast and simple stretch-minimizing mesh parameterization. In: Proceedings of the Shape Modeling International 2004, pp. 200–208. IEEE Computer Society, Washington, DC (2004). doi: 10.1109/SMI.2004.2
  36. 36.
    Yusov, E., Shevtsov, M.: High-performance terrain rendering using hardware tessellation. WSCG 19(3), 85–92 (2011)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  • HyeongYeop Kang
    • 1
  • Hanyoung Jang
    • 2
  • Chang-Sik Cho
    • 3
  • JungHyun Han
    • 1
  1. 1.Computer Science and EngineeringKorea UniversitySeoulKorea
  2. 2.NCsoftSeongnamKorea
  3. 3.Electronics and Telecommunications Research InstituteDaejeonKorea

Personalised recommendations