Quick-VDR: Interactive View-Dependent Rendering of Massive Models

1. Quick-VDR: Interactive View-Dependent Rendering of Massive Models Sung-Eui Yoon Brian Salomon Russell Gayle Dinesh Manocha University of North Carolina at Chapel Hill http://gamma.cs.unc.edu/QVDR

2. Goal • Interactive display of complex and massive models at high image fidelity • Models from CAD, scientific simulation, and scanning devices • High primitive counts • Irregular distribution of geometry

3. CAD Model – Power Plant 12 million triangles Irregular distribution Large occluders

4. Isosurface from Turbulence Simulation (LLNL) 100 million triangles High depth complexity Small occluders Many holes

5. Scanned Model –St. Matthew 372 million triangles Highly tessellated

6. Problems of current representation • High cost of refining and rendering the geometry • High memory footprint • Complicate integration with other techniques • occlusion culling and out-of-core management

7. Main Contribution • New view-dependent rendering algorithm Clustered Hierarchy of Progressive Meshes (CHPM) Out-of-core construction and rendering Integrating occlusion culling and out-of-core management

8. Realtime Captured Video – Power plant Pentium IV GeForce FX 6800 Ultra 1 Pixel of Error

9. Previous Work • Geometric simplification • View-dependent simplification • Out-of-core simplification • Occlusion culling • Hybrid algorithms

10. Geometric Simplification • Static [Cohen et al. 96 and Erikson et al. 01] • View-dependent [Hoppe 97; Luebke et al. 97; Xia and Varshney 97] • Surveyed in Level of Detail book[Luebke el al. 02]

11. View-Dependent Simplification • Progressive mesh [Hop96] • Merge tree [Xia and Varshney 97] • View-dependent refinement of progressive meshes [Hoppe 97] • Octree-based vertex clustering [Luebke and Erikson 97] • View-dependent tree [El-Sana and Varshney 99] • Out-of-core approaches [Decoro and Pajarola 02; Lindstrom 03]

12. Out-of-core Simplification • Static [Lindstrom and Silva 01; Shaffer and Garland 01; Cignoni et al. 03] • Dynamic [Hoppe 98; Prince 00; El-Sana and Chiang 00; Lindstrom 03]

13. Occlusion Culling • A recent survey is in [Cohen-Or et al. 03] • Image-based occlusion representation • [Greene et al 93, Zhang et al, 97, Klosowski and Silva 01] • Additional graphics processors • [Wonka et al. 01, Govindaraju et al. 03]

14. Hybrid Approaches • Combine model simplification and occlusion culling techniques • UC Berkeley Walkthrough[Funkhouser 96] • UNC MMR system[Aliaga 99] • Integrate occlusion culling with view dependent rendering • [El-Sana et al. 01; Yoon et al. 03]

15. Outline • CHPM representation • Building a CHPM • Interactive display • Implementation and results • Conclusion and future work

16. Outline • CHPM representation • Building a CHPM • Interactive display • Implementation and results • Conclusion and future work

17. Clustered Hierarchy of Progressive Meshes (CHPM) • Novel view-dependent representation • Cluster hierarchy • Progressive meshes PM3 PM1 PM2

18. Clustered Hierarchy of Progressive Meshes (CHPM) • Cluster hierarchy • Clusters are spatially localized mesh regions • Used for visibility computations and out-of-core rendering

19. Clustered Hierarchy of Progressive Meshes (CHPM) • Progressive mesh (PM) [Hoppe 96] • Each cluster contains a PM as an LOD representation Vertex splits PM: Base mesh

20. Two-Levels of Refinement • Coarse-grained view-dependent refinement • Provided by selecting a front in the cluster hierarchy Front

21. Two-Levels of Refinement • Coarse-grained view-dependent refinement • Provided by selecting a front in the cluster hierarchy Cluster-split

22. Two-Levels of Refinement • Coarse-grained view-dependent refinement • Provided by selecting a front in the cluster hierarchy Cluster-split Cluster-collapse

23. Vertex split 0 Vertex split 1 ….. Vertex split n Two-Levels of Refinement • Fine-grained local refinement • Supported by performing vertex splits in PMs PM

24. Simplification Error Bound • Conservatively compute object space error bound given screen space error bound • Perform two-levels of refinement based on the error bound

25. Main Properties of CHPM • Low refinement cost • 1 or 2 order of magnitude lower than a vertex hierarchy • Alleviates visual popping artifacts • Provides smooth transition between different LODs

26. Video – Comparison CHPM with Vertex Hierarchy

27. Outline • CHPM representation • Building a CHPM • Interactive display • Implementation and results • Conclusion and future work

28. Overview of Building a CHPM Input model Cluster decomposition Performed in out-of-core manner Cluster hierarchy generation Hierarchical simplification CHPM

29. Overview of Building a CHPM Input model Cluster decomposition Cluster hierarchy generation Hierarchical simplification CHPM

30. Cluster Decomposition • Cluster • Main unit for view-dependent refinement, occlusion culling, out-of-core management • Spatially localized portion of the mesh • Equally sized in terms of number of triangles

31. Cluster Decomposition • Similar to [Ho et al. 01; Isenburg and Gumhold 03] Graph between cells

32. An Example of Cluster Decomposition Each cluster contains 4K triangles

33. Overview of Building a CHPM Input model Cluster decomposition Cluster hierarchy generation Hierarchical simplification CHPM

34. Cluster Hierarchy Generation - Properties • Nearly equal cluster size • High spatial locality • Minimum shared vertices • Balanced cluster hierarchy

35. Cluster Hierarchy Generation - Algorithm • Node • Corresponds to a cluster • Weighted by the number of vertices • Edge • Made if clusters share vertices • Weighted by the number of shared vertices

36. Cluster Hierarchy Generation - Algorithm 2nd level clusters Root cluster 3rd level clusters Leaf clusters

37. Overview of Building a CHPM Input model Cluster decomposition Cluster hierarchy generation Hierarchical simplification CHPM

38. Out-of-core Hierarchical Simplification • Simplifies clusters in a bottom-up manner

39. Out-of-core Hierarchical Simplification • Simplifies clusters in a bottom-up manner PM5 PM4 PM1 PM3 PM2

40. A B C D dependency E F C A B D Cluster hierarchy Boundary Simplification Boundary constraints

41. A B C D dependency E F C A B D Cluster hierarchy Boundary Simplification E F

42. Boundary Constraints • Common problem in many hierarchical simplification • [Hoppe 98; Prince 00; Govindaraju et al. 03] • Degrades the quality of simplification • Decrease rendering performance at runtime • Aggravated as a depth of hierarchy increases

43. Boundary Constraints

44. Boundary Constraints

45. Cluster Dependencies • Replaces preprocessing constraints by runtime dependencies

46. E F A B C D Cluster Dependencies dependency E F C A B D Cluster hierarchy

47. E F A B C D Cluster Dependencies dependency E F C A B D Cluster hierarchy

48. Cluster Dependencies at Runtime Force cluster-split Cluster-split dependency E F C A B D Cluster hierarchy

49. Cluster Dependencies 92% triangles reduced 227K triangles 19K triangles After posing cluster dependencies

50. Outline • CHPM representation • Building a CHPM • Interactive display • Implementation and results • Conclusion and future work