Journal of Visualization

, Volume 20, Issue 2, pp 379–391 | Cite as

Reconstructing flicker-free surfaces in hybrid particle-grid water simulation

Robust tracking of fluid surfaces using dual marching cubes
  • Jong-Hyun Kim
  • Chang-Hun Kim
  • Jung LeeEmail author
Regular Paper


We present a new method for adaptively extracting flicker-free surfaces from time-varying nonuniform point-set data such as a hybrid particle–grid water simulation. When particles are irregularly distributed in hybrid simulations, degenerate triangles and holes may occur when constructing surfaces adaptively. These abnormal surfaces appear unexpectedly between frames, and we call them “flicker” artifacts (see Fig. 1). In this paper, we address this problem by developing: (1) a kernel-based octree technique to avoid degenerate triangles being created because of size discontinuities between adjacent leaf cells; (2) a level-set error compensation algorithm to avoid apertured water surfaces caused by some particles being lost in the triangulation process; and (3) the extraction of sufficient surface particles for efficient reconstruction of surfaces with extreme amounts of spatial adaptivity. Comparisons with previous methods convincingly demonstrate that our technique successfully reduced flicker artifacts.

Graphical abstract


Flicker-free surfaces Surface reconstruction Physically based animation Dual marching cubes 



This research was supported by a Korea University Grant and Hallym University Research Fund (HRF-201609-008), Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education, Science and Technology (NRF-2013R1A1A2011602). This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education, Science, ICT and future Planning(NRF-2014R1A2A2A01007143, NRF-2015R1C1A2A01053543, NRF- 2015R1A2A1A16074940, NRF-2015R1A1A1A05001196).


  1. Akinci G, Akinci N, Oswald E, Teschner M (2013) Adaptive surface reconstruction for SPH using 3-level uniform grids. In: international conferences in Central Europe on computer graphics, visualization and computer vision, pp 195–204Google Scholar
  2. Akinci G, Ihmsen M, Akinci N, Teschner M (2012) Parallel surface reconstruction for particle-based fluids. Comput Graph Forum 31(6):1797–1809CrossRefGoogle Scholar
  3. Akinci N, Cornelis J, Akinci G, Teschner M (2013) Coupling elastic solids with SPH fluids. Comput Anim Virtual Worlds 24(3–4):195–203CrossRefGoogle Scholar
  4. Akinci N, Ihmsen M, Akinci G, Solenthaler B, Teschner M (2012) Versatile rigid-fluid coupling for incompressible SPH. ACM Trans Graph 31(4):62:1–62:8CrossRefGoogle Scholar
  5. Ando R, Thurey N, Tsuruno R (2012) Preserving fluid sheets with adaptively sampled anisotropic particles. IEEE Trans Vis Comput Graph 18(8):1202–1214CrossRefGoogle Scholar
  6. Ando R, Thürey N, Wojtan C (2013) Highly adaptive liquid simulations on tetrahedral meshes. ACM Trans Graph 32(4):103:1–103:10CrossRefzbMATHGoogle Scholar
  7. Ando R, Tsuruno R (2011) A particle-based method for preserving fluid sheets. ACM SIGGRAPH Eurograph Symp Comput Anim 10:7–16Google Scholar
  8. Becker M, Ihmsen M, Techner M (2009) Corotated SPH for deformable solids. In: Eurographics workshop on natural phenomena, pp 27–34Google Scholar
  9. Becker M, Teschner M (2007) Weakly compressible SPH for free surface flows. In: ACM SIGGRAPH/Eurographics symposium on computer animation, pp 209–217Google Scholar
  10. Becker M, Tessendorf H, Teschner M (2009) Direct forcing for Lagrangian rigid-fluid coupling. IEEE Trans Vis Comput Graph 15(3):493–503CrossRefGoogle Scholar
  11. Cornelis J, Ihmsen M, Peer A, Teschner M (2014) IISPH-FLIP for incompressible fluids. Comput Graph Forum 33(2):255–262CrossRefGoogle Scholar
  12. Elseberg J, Borrmann D, Nüchter A (2013) One billion points in the cloud an octree for efficient processing of 3D laser scans. J Photogramm Remote Sens 76:76–88CrossRefGoogle Scholar
  13. Foster N, Fedkiw R (2001) Practical animation of liquids. ACM transactions on graphics, pp 23–30Google Scholar
  14. Holmlid E (2010) Manifold contouring of an adaptively sampled distance fieldGoogle Scholar
  15. Ihmsen M, Cornelis J, Solenthaler B, Horvath C, Teschner M (2014) Implicit incompressible SPH. IEEE Trans Vis Comput Graph 20(3):426–435CrossRefGoogle Scholar
  16. Ju T, Losasso F, Schaefer S, Warren J (2002) Dual contouring of hermite data. ACM Trans Graph 21(3):339–346CrossRefGoogle Scholar
  17. Kim JH, Kim CH, Lee J (2015) A hybrid sdf for the detailed representation of liquid–solid mixed surfaces. Comput Anim Virtual WorldsGoogle Scholar
  18. Kim PR, Lee HY, Kim JH, Kim CH (2012) Controlling shapes of air bubbles in a multi-phase fluid simulation. Vis Comput 28(6–8):597–602CrossRefGoogle Scholar
  19. Lenaerts T, Adams B, Dutré P (2008) Porous flow in particle-based fluid simulations. ACM Trans Graph 27(3)Google Scholar
  20. Lenaerts T, Dutré P (2008) Unified SPH model for fluid-shell simulations. In: ACM SIGGRAPH Posters, pp 12–13Google Scholar
  21. Löffler F, Rybacki S, Schumann H (2009) Error-bounded gpu-supported terrain visualisation. In: International conferences in Central Europe on computer graphics, visualization and computer vision. Václav Skala-UNION AgencyGoogle Scholar
  22. Löffler F, Schumann H (2010) Qem-filtering: a new technique for feature-sensitive terrain mesh simplification. In: International workshop on vision, modeling and visualization, pp 1–8Google Scholar
  23. Löffler F, Schumann H (2012) Generating smooth high-quality isosurfaces for interactive modeling and visualization of complex terrains. In: Proceedings of the vision, modeling, and visualization workshopGoogle Scholar
  24. Löffler F, Schwanke S, Schumann H (2010) A hybrid approach for high quality real-time terrain rendering and optimized a-priori error estimation. In: Proceedings of the international conference on computer graphics theory and applications, pp 233–238Google Scholar
  25. Losasso F, Gibou F, Fedkiw R (2004) Simulating water and smoke with an octree data structure. ACM Trans Graph 23(3):457–462CrossRefGoogle Scholar
  26. Macklin M, Müller M (2013) Position based fluids. ACM Trans Graph 32(4):104:1–104‘:12CrossRefzbMATHGoogle Scholar
  27. Müller M, Charypar D, Gross M (2003) Particle-based fluid simulation for interactive applications. ACM SIGGRAPH Eurographics Symp Comput Anim 6:154–159Google Scholar
  28. Müller M, Keiser R, Nealen A, Pauly M, Gross M, Alexa M (2004) Point based animation of elastic, plastic and melting objects. In: ACM SIGGRAPH/Eurographics symposium on computer animation, pp 141–151Google Scholar
  29. Müller M, Schirm S, Teschner M, Heidelberger B, Gross M (2004) Interaction of fluids with deformable solids. Comput Anim Virtual Worlds 15(3–4):159–171CrossRefGoogle Scholar
  30. Müller M, Solenthaler B, Keiser R, Gross M (2005) Particle-based fluid-fluid interaction. In: ACM SIGGRAPH/Eurographics symposium on computer animation, pp 237–244Google Scholar
  31. Nielson GM (2004) Dual marching cubes. In: Proceedings of the conference on visualization’04, pp 489–496Google Scholar
  32. Ohtake Y, Belyaev A, Alexa M, Turk G, Seidel HP (2003) Multi-level partition of unity implicits. ACM Trans Graph 22(3):463–470CrossRefGoogle Scholar
  33. Park T, Lee H, Kim Ch (2007) Progressive compression of geometry information with smooth intermediate meshes. Pattern recognition and image analysis. Springer, Berlin, pp 89–96CrossRefGoogle Scholar
  34. Schaefer S, Warren J (2005) Dual marching cubes: primal contouring of dual grids. Comput Graph Forum 24(2):195–201CrossRefGoogle Scholar
  35. Sim JY, Lee SU, Kim CS (2005) Construction of regular 3D point clouds using octree partitioning and resampling. IEEE Int Symp Circuits Syst 2005(2):956–959Google Scholar
  36. Solenthaler B, Gross M (2011) Two-scale particle simulation. ACM Trans Graph 30(4):81:1–81:8CrossRefGoogle Scholar
  37. Solenthaler B, Pajarola R (2008) Density contrast SPH interfaces. In: ACM SIGGRAPH/Eurographics symposium on computer animation, pp 211–218Google Scholar
  38. Solenthaler B, Pajarola R (2009) Predictive–corrective incompressible SPH. ACM Trans Graph 28(3):40–46CrossRefGoogle Scholar
  39. Solenthaler B, Schlafli J, Pajarola R (2007) A unified particle model for fluid solid interactions. Comput Anim Virtual Worlds 18(1):69–82CrossRefGoogle Scholar
  40. Thürey N, Keiser R, Pauly M, Rüde U (2006) Detail-preserving fluid control. In: ACM SIGGRAPH/Eurographics symposium on computer animation, pp 7–12Google Scholar
  41. Um K, Baek S, Han J (2014) Advanced hybrid particle-grid method with sub-grid particle correction. Comput Graph Forum 33(7):209–218CrossRefGoogle Scholar
  42. Wang CB, Zhang Q, Kong FL, Qin H (2013) Hybrid particle-grid fluid animation with enhanced details. Vis Comput 29(9):937–947CrossRefGoogle Scholar
  43. Yang L, Li S, Hao A, Qin H (2012) Realtime two-way coupling of meshless fluids and nonlinear fem. Comput Graph Forum 31(7):2037–2046CrossRefGoogle Scholar
  44. Zhu Y, Bridson R (2005) Animating sand as a fluid. ACM Trans Graph 24(3):965–972CrossRefGoogle Scholar

Copyright information

© The Visualization Society of Japan 2016

Authors and Affiliations

  1. 1.Korea UniversitySeongbuk-guRepublic of Korea
  2. 2.Hallym UniversityChuncheonRepublic of Korea

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