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Point-based Modeling
Alexa et al., 2001
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Rubin & Whitted, SIGGRAPH 1980
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Navigating Point Clouds
• Consistent normals?• Inside and outside?• Signed distance?
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From [Hoppe et al., 1992]
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From [Hoppe et al., 1992]
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From [Hoppe et al., 1992]
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Rendering Point-based Models
• Surfels, or surface elements• Splatting
– one surfel maps to many pixels
• Two demos:– QSplat [Rusinkiewicz et al, 2000]
– Surfels… PointShop
• Sampling details … later
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Modeling with Point Set Surfaces
• Point set surfaces:– implicit connectivity info– no fixed continuity class
• Moving Least Squares (MLS) surfaces– High quality C∞ surfaces– Noise & redundancy reduction– Progressive representations, etc.
Alexa et al., 2001
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References
• David Levin, The approximation power of moving least-squares, Mathematics of Computation, 76(224), 1998.– David Levin, Mesh-independent surface interpolation, To
appear in "Geometric Modeling for Scientific Visualization" Edited by Brunnett, Hamann and Mueller, Springer-Verlag, 2003.
• M. Alexa, J. Behr, D. Cohen-Or, S. Fleishman, D. Levin and C. T. Silva, Point Set Surfaces, IEEE Visualization 2001. pp. 21-28, 2001.
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Details: Moving Least Squares (MLS) Approximations
• MLS: Nonlinear projection procedure• Goal project a point "r" onto surface• Two steps:
1. Define local reference domain (plane)2. Build local polynomial map
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MLS
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Smoothing and the "h" parameter
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Noise Reduction
• MLS projects points onto smooth MLS 2-manifold
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Down-sampling
• Useful for compact building models
• Process similar to polyhedral simplification
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Up-sampling• Refine point set to
achieve desired density• Using local approximation
of Voronoi diagram
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Surfel Sampling using LDC Trees
Reference:Hanspeter Pfister, Matthias Zwicker, Jeroen van Baar, Markus Gross.Surfels: Surface Elements as Rendering PrimitivesProceedings of ACM SIGGRAPH 2000. pp. 335-342, 2000.
Some slides from:IEEE Visualization 2001 TutorialPoint-Based Computer Graphics and Visualization Instructor: Hanspeter Pfister ([email protected])
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Surfel Sampling using LDC Trees
• Need guarantee on sampling density– Low dispersion sampling
• Pseudo image space approach• LDC Tree…
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“3-to-1 Reduction”
• Reduce LDC to one LDI– Name “3-to-1 reduction” due to rendering speedup
• Nearest neighbor interpolation– Quantized positions, normals (look-up table), materials, …
• Better surfel density
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