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Nov 23, 2022 332 likes •632 views

Interactive Rendering of Large Unstructured Grids Using Dynamic Level-of-Detail Steven P. Callahan , Joo L. D. Comba Peter Shirley , and Cludio T. Silva University of Utah UFRGS, Brazil Dynamic Level-of-Detail 100%

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Interactive Rendering of Large Unstructured Grids Using Dynamic Level-of-Detail

Steven P. Callahan†, João L. D. Comba‡ Peter Shirley†, and Cláudio T. Silva†

† University of Utah ‡ UFRGS, Brazil

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Dynamic Level-of-Detail 100% 2.0 fps 5% 16.1 fps 25% 5.3 fps

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Level-Of-Detail Background

➤ Geometric Approach

[Cignoni et al. 2004]

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Level-Of-Detail Background

➤ Texture Approach

[Leven et al. 2002]

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Level-Of-Detail Background

➤ Tetrahedra

  • Farias et al. 2000
  • Leven et al. 2002
  • Cignoni et al. 2004
  • Museth and Lombeyda 2004

➤ Regular Grids

  • Danskin and Hanrahan 1992
  • LaMar et al. 1999
  • Weiler et al. 2000

➤ Triangles or Points

  • Funkhouser and Séquin 1993
  • Luebke and Erikson 1997
  • Luebke et al. 2002
  • Duessen et al. 2002
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Definitions Given a scalar field An approximation can be made such that and . A ray passing through the domain forms a continuous function

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Domain-Based Simplification

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Sample-Based Simplification

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Triangle Sampling

➤ Sample the triangles

  • Boundary + Internal triangles

LOD B1,B2,...,Bn I1,I2,...,Im

➤ LOD index updated at each pass

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Hardware-Assisted Visibility Sorting

➤ Sort in object-space and image-space

CPU GPU

[Callahan et al. 2005, Silva et al. 2005]

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Hardware-Assisted Dynamic Level-of-Detail

CPU GPU

➤ Sample in object-space

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Ranking Strategies Topology: target continuity

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Ranking Strategies Field: target histogram

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Ranking Strategies View: target screen-space coverage

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Ranking Strategies Area: target faces that cause greater error

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Visual Quality 100% 1.3 fps 15% 4.5 fps 5% 10.0 fps

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Movie

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Movie

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Movie

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Preprocessing 15.3 s 15.3s 13.9 s 75.6 s 1.4 M Fighter 11.2 s 11.6 s 10.5 s 87.2 s 1.0 M Torso 13.9 s 5.3 s 4.5 s 17.8 s 0.8 M Spx2 Area View Field Topology Tets Dataset

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Strategy Analysis

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Strategy Analysis

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Strategy Analysis

Full Quality Topology View Field Area

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Domain and Sample Comparison Full Quality

100% @ 20 fps

Sample

50% @ 30 fps

Domain

50% @ 23 fps

g(t) g1(t) g2(t) t t t

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g(t) g1(t) g2(t) t t

Domain and Sample Comparison Full Quality

100% @ 20 fps

Sample

50% @ 30 fps

Domain

25% @ 30 fps

t

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g(t) g1(t) g2(t) t t

Domain and Sample Comparison Full Quality

100% @ 20 fps

Domain

1% @ 60 fps

Sample

10% @ 60 fps

t

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Conclusion

➤ New sampling approach which simplifies LOD ➤ Well-suited for a GPU implementation ➤ Dynamic changes to LOD are simple and require no explicit

hierarchies

➤ Tetmesh 0.1 code will be available soon at

www.sci.utah.edu/~vgc

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Open Research

➤ Better ranking strategies ➤ Handle even larger data

  • Sample the boundaries
  • Sample points instead of triangles

➤ Adaptive time-varying visualization

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Acknowledgments

➤ Carlos Scheidegger , Huy Vo, and John Schreiner ➤ Datasets

  • Bruno Notrosso (Electricite de France)
  • Neely and Batina (NASA)
  • SCI Institute, University of Utah

➤ Funding

  • DOE
  • CNPq
  • MICS
  • NSF
  • University of Utah