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Displaced Subdivision Surfaces

Displaced Subdivision Surfaces. Aaron Lee Princeton University. Hugues Hoppe Microsoft Research. Henry Moreton Nvidia. Triangle Meshes. Interactive animation Adaptive rendering Compact storage. Dataset provided by Cyberware. mesh simplification. Scalable Algorithms.

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Displaced Subdivision Surfaces

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  1. Displaced Subdivision Surfaces Aaron Lee Princeton University Hugues Hoppe Microsoft Research Henry Moreton Nvidia

  2. Triangle Meshes • Interactive animation • Adaptive rendering • Compact storage Dataset provided by Cyberware

  3. mesh simplification Scalable Algorithms • Multiresolution now well established subdivision surfaces

  4. Subdivision Surfaces • Smooth with arbitrary topology • No stitching of patches • Easy Implementation • Simple subdivision rules • Level-of-detail rendering • Uniform or adaptive subdivision

  5. Our Approach DSS = Smooth Domain  Scalar Disp Field Displaced Subdivision surface Control mesh Domain Surface

  6. Representation Overview Piecewise-regular mesh of scalar displacement sampling pattern Control mesh

  7. Advantages of DSS • Intrinsic parameterization • Governed by a subdivision surface • No storage necessary • Significant computation efficiency • Capture detail as scalar displacement • Unified representation • Same sampling pattern and subdivision rules for geometry and scalar displacement field

  8. Conversion Algorithm • Control mesh creation • Control mesh optimization • Scalar displacement computation • Attribute resampling

  9. Control Mesh Creation Mesh Simplification Normal Cone Constraint Original Mesh Initial Control Mesh [Garland 97] Surface simplification using quadric error metrics

  10. Normal Cone Constraint allowable normals on Gauss sphere

  11. Tracking Correspondences • Control Mesh Creation • mesh simplification 11776 faces 120 faces [Lee 98] Multiresolution Adaptive Parameterization of Surfaces

  12. Conversion Process 1. Obtain an initial control mesh by simplifying the original mesh. 2.Globally optimize the control mesh vertices. 3.Sample the displacement map and computr the signed displacement .

  13. Control Mesh Creation Mesh Simplification Normal Cone Constraint Original Mesh Initial Control Mesh

  14. Control Mesh Optimization Global Optimization Initial Control Mesh Optimized Control Mesh

  15. Scalar Displacement Computation Scalar Displacement Field Smooth Domain Surface Displaced Subdivision Surface

  16. Attribute Resampling DSS With Scalar Displacement Field DSS with Resampled Texture Original mesh

  17. Applications • Editing • Animation • Bump mapping • Adaptive tessellation • Compression

  18. Editing

  19. Animation Polyhedral Domain Surface (e.g. Gumhold-Hüttner 99) Smooth Domain Surface (DSS)

  20. Animation

  21. Bump Mapping • Explicit geometry Bump map 134,656 faces 8,416 faces 526 faces [Blinn 78] Simulation of wrinkled surfaces

  22. Adaptive Tessellation

  23. Compression Scalar Displacement field Quantizer Entropy Coder M0 Quantizer Entropy Coder Delta encoding with Linear Prediction M1 Bit Allocation Quantizer Entropy Coder Mk

  24. Compression (Venus) [Venus Raw Data] 1,800,032 bytes

  25. Compression (Dinosour)

  26. Conclusion • DSS Representation: • Unified representation • Simple subdivision rules • Analytic surface properties • Applications • Editing • Animation • Bump mapping • Adaptive tessellation • Compression

  27. Timings and Results Scalar field creation Simplification Input size # Base Optimization Dataset #triangles domain (mins) (mins) (mins) triangles Armadillo 1306 210,944 61 25 2.5 Venus 748 28 11 2 100,000 1.3 Bunny 69,451 526 19 12 4.6 43 342,138 1564 115 Dinosaur

  28. over

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