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Multiresolution Analysis of Irregular Meshes with Multiple Attributes

Michaël Roy. Multiresolution Analysis of Irregular Meshes with Multiple Attributes. 3D Models. High quality 3D models High density meshes High resolution textures Available ressources are always constrained CPU, space, graphics speed, network bandwidth

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Multiresolution Analysis of Irregular Meshes with Multiple Attributes

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  1. Michaël Roy Multiresolution Analysis of Irregular Meshes withMultiple Attributes

  2. 3D Models High quality 3D models High density meshes High resolution textures Available ressources are always constrained CPU, space, graphics speed, network bandwidth We need an efficient mesh representation

  3. Motivations (1) Level of Detail Representation Adaptive representation Varies with context Picture of the original object Level 0 117,564 faces (initial scan) Level 5 25,100 faces Level 10 5,232 faces Level 15 1,066 faces Level 20 212 faces

  4. Motivations (2) Multiresolution Analysis Space / Frequency analysis of 3D models Filtering Small scale detail: high frequency Large scale detail: low frequency min max

  5. Wavelet Transform (1) V0 V1 W1 V2 W2 V3 W3 Vi Wi Synthesis(Reconstruction) Analysis(Decomposition) Approximation Details

  6. Wavelet Transform (2) Decomposition A0 A1 Aj-1 V0 V1 V2 Vj-1 Vj B0 B1 Bj-1 W1 Wj W2 Reconstruction Pj Pj-1 P1 Vj-1 Vj-2 V0 Vj V1 Qj Qj-1 Q1 Wj W1 Wj-1

  7. Previous Work (1) Coarse-to-fine hierarchies Lounsbery 1995Multiresolution for surface of arbitrary topological type Zorin 1997Interactive Multiresolution Mesh Editing

  8. Previous Work (2) Fine-to-coarse hierarchies Bonneau 1998Multiresolution Analysis on Irregular Meshes Guskov 1999Multiresolution Signal Processing for Meshes

  9. Multiresolution Analysis Framework Level of detail representation Detail extraction 3D model with attributes Multiresolution Analysis Multiresolution model Intelligent visualization Filtering Denoising Characterisation

  10. Level of detail representation Simplification Level 0 117,564 faces Level 5 25,100 faces Level 10 5,232 faces Level 15 1,066 faces Level 20 212 faces Subdivision

  11. Progressive Mesh (Hoppe 1996) Edge contraction Vertex split econ1 econj-2 econj-1 econ0 ... Mj-1 M0 M1 Mj vsplit1 vsplitj-2 vsplitj-1 vsplit0

  12. Progressive Mesh (Hoppe 1996) Pro: Nested mesh hierarchy Vj Vj-1  ...  V1  V0 Edge contraction Vertex split

  13. Progressive Mesh (Hoppe 1996) Con: only one vertex removed per level Edge contraction Vertex split

  14. Global Downsampling Create distinct levels of detail Select an independent set of vertices and remove them by a serie of edge contractions Fine mesh Select vertices to remove Coarse mesh

  15. Detail Computation Details are the difference between a fine mesh and a smoothed version of that mesh Original Smoothed Difference

  16. Surface Relaxation Smooth the surface using a relaxation operator minimizing the curvature

  17. Attribute Details What about the attributes ? Attribute details are the difference between the attributes of a fine mesh and the smoothed attributes of that mesh Original Smoothed Difference

  18. Surface Attribute Relaxation Smooth the attributes using a relaxation operator minimizing the curvature Assume the attributes are linked to the surface

  19. Multiresolution Mesh Decomposition Fine model with attributes Vertex Selection Attribute Surface Relaxation Simplification _ + Coarse model Details

  20. Multiresolution Mesh Reconstruction Coarse model Details Subdivision Attribute Surface Relaxation + + Fine model

  21. Applications Level of detail representation Detail extraction 3D model with attributes Multiresolution Analysis Multiresolution model Characterisation Intelligent visualization Filtering Denoising

  22. Filtering

  23. Denoising (1) We extend the concept of soft thresholding (AKA wavelet shrinkage) to 3D multiresolution model

  24. Denoising (2) Initial model Laplacian smoothing Soft thresholding

  25. Denoising (3)

  26. Characterization (1) Thresholding the detail allows highlight of important features of a model

  27. Characterization (2) Impulse Noise Detection Impulse noise Geometric analysis Normal analysis Noise detection Impulse Noise Detection

  28. Intelligent Visualization (1) Level Vs Threshold Reconstruction Threshold reconstruction selects vertices according to their details

  29. Intelligent Visualization (2) 131 242 faces (6.8 MB) 36 772 faces (1.9 MB)

  30. Intelligent Visualization (3) Initial model (73.000 faces) Level reconstruction (17.000 faces) Threshold reconstruction (16.000 faces)

  31. Conclusion Multiresolution decomposition for irregular meshes with attributes Global downsampling Attribute surface relaxation Applications Filtering Denoising using soft thresholding Characterization / feature detection Adaptive reconstruction

  32. Future Work Improve characterization Use the angle between the normal and the detail vector Visualization of meshes with multiple attributes Management of multiple attributes Investigation for better detail metrics e.g. HSI space for colors

  33. Multiresolution Mesh Analysis Thank you for your attention ! Questions ?

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