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Assessment of Mesh Simplification Algorithm Quality

Assessment of Mesh Simplification Algorithm Quality. Michaël ROY, Frédéric NICOLIER , Sebti FOUFOU , Frédéric TRUCHETET, Andreas KOSCHAN, Mongi ABIDI. Outline. Introduction Mesh Mesh simplification Quality metrics Quality assessment Geometric deviation Attribute deviation Results

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Assessment of Mesh Simplification Algorithm Quality

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  1. Assessment of Mesh Simplification Algorithm Quality Michaël ROY, Frédéric NICOLIER, Sebti FOUFOU, Frédéric TRUCHETET, Andreas KOSCHAN, Mongi ABIDI

  2. Outline • Introduction • Mesh • Mesh simplification • Quality metrics • Quality assessment • Geometric deviation • Attribute deviation • Results • Conclusion and future work

  3. Mesh • Geometrical data • Vertices • Faces • Appearance data • Colors • Normals • Texture coordinates

  4. Mesh Synthetic mesh Digital elevation map

  5. Mesh simplification • High quality / big meshes • High vertex & face number • Motivations • Interactive manipulation • Low space storage • Quick network transmission

  6. Mesh simplification 60 000 faces Original mesh Simplified mesh 1 000 faces

  7. Quality metrics • Geometric error METRO -P. Cignoni, C. Rocchini, R. Scopigno (1998)

  8. Quality metrics • Geometric error - METRO 1998 • Point-to-surface distance P: a point S: a surface d(p,p’) : Euclidian distance between two points in R3

  9. Quality metrics • Texture deviation - Cohen (1998) Original mesh Simplified mesh

  10. Quality metrics • Texture deviation- Cohen (1998) S1 etS2: two surfaces pi: a point onS1 F(p) = (s,t) : texture coordinates of the point p F-1(s,t) = p : point with texture coordinates(s,t)

  11. Quality metrics • Texture deviation- Cohen (1998) If no real texture deviation Cohen’s texture deviation = geometric deviation Conclusion: not suitable for assessing mesh simplification quality

  12. Quality assessment Two measurements • Geometric deviation • Attribute deviation

  13. Geometric deviation

  14. Geometric deviation M1et M2: two meshes S1 etS2: their respective surfaces pi: a point on surfaceS1

  15. Attribute deviation Original mesh Simplified mesh

  16. Attribute deviation M1et M2: two meshes S1 etS2: their respective surface pi: a point on surfaceS1 A(p) = av: attribute at point p N(p,S) = pc: nearest pointto point pon surface S

  17. Implementation • Find the nearest point • Uniform grid • Uniform distributed point on surface • Surface sampling • Deviation texture • Texture packing

  18. Results • Mesh simplification algorithm used • Qslim 2.0 (Garland 98) • Jade 2.1 (Ciampalini, Cignoni 97) • ProgMesh 1.2 (Hoppe 96)

  19. Results • Test mesh 53 696 faces 1 073 faces

  20. Results QSlim Jade ProgMesh Geometric deviation Normal deviation

  21. Results

  22. Results

  23. Results

  24. Results Original Simplified (L) Simplified (H) Geometric Cohen (L) Cohen (H) Attribute (L) Attribute (H)

  25. Conclusion and future work • Quality assessment • Geometric deviation • Attributes deviation • Results on three simplification algorithms • Software: http://meshdev.sourceforge.net • Future : • Adapt attribute deviation to the color space • Estimate triangulation quality

  26. Assessment of Mesh Simplification Algorithm Quality Michaël ROY, Frédéric NICOLIER, Sebti FOUFOU, Frédéric TRUCHETET, Andreas KOSCHAN, Mongi ABIDI

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