decimating samples for mesh simplification
DESCRIPTION
Decimating Samples for Mesh Simplification. Surface Reconstruction. A sample and PL approximation. Sample Decimation. Original 40K points. = 0.33 12K points. = 0.4 8K points. Local feature size and sampling. Medial axis Local feature size f(p). -sampling d(p)/f(p). - PowerPoint PPT PresentationTRANSCRIPT
Decimating Samples for Mesh Simplification
Surface Reconstruction
• A sample and PL approximation
Sample Decimation
Original40K points
= 0.48K points
= 0.3312K points
Local feature size and sampling
• Medial axis
• Local feature size f(p)
• -sampling
• d(p)/f(p)
Voronoi structures
Cocones
• Compute cocones
• Filter triangles whose duals intersect cocones
• Extract manifold
Space spanned by vectors making angle /8 with horizontal
Cocones, radius and height•cocones:C(p,,v) space by vectors making /2 - with a vector v.
• radius r(p): radius of cocone
• height h(p): min distance to the poles
Decimate
Cocone Lemma
Guarantees
Foot
Original20021 points
0.42046 points
0.332714 points
Foot
0.42046 points
0.332714 points
0.254116 points
Bunny
0.47K points
0.3311K points
Original35K points
Bunny
0.47K points
0.3311K points
Original35K points
Experimental Data
Conclusions• Introduced a measure radius/height ratio for skininess of Voronoi cells
• We have used the radius/height ratio for sample decimation
• Used it for boundary detection (SOCG01)
• What about decimating supersize data (PVG01)
• Can we use it to eliminate noise?
• www.cis.ohio-state.edu/~tamaldey
543,652 points143 -> 28 min
3.5 million pointsUnfin-> 198 min