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Mesh Modelling With Curve Analogies

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Mesh Modelling With Curve Analogies. Steve Zelinka. Michael Garland ... Reduce artistic skill required for modelling. Solution: Modelling by Analogy. A : A' :: B : ... – PowerPoint PPT presentation

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Title: Mesh Modelling With Curve Analogies


1
Mesh Modelling With Curve Analogies
  • Steve ZelinkaMichael Garland
  • University of Illinois at Urbana-Champaign

2
In a Nutshell
3
Overview
  • Motivation
  • Related Work
  • Details of our Approach
  • Curve Selection
  • Surface Transformation
  • Results
  • Future Work

4
Motivation
  • Reduce artistic skill required for modelling
  • Solution Modelling by Analogy A
    A B ?
  • Images Hertzmann et al 2001
  • Curves Hertzmann et al 2002

5
Mesh Analogies?
  • User burden
  • Unsolved technical issues

  • ?

6
Related Work
  • Geometric texture synthesis Bhat et al
    2004 Lagae et al 2004

7
Related Work
  • Common parameterizations Kraevoy and Sheffer
    2004 Schreiner et al 2004 Allen et al 2003
  • Deformation transfer Sumner and Popovic 2004

8
Related Work
  • Multiresolution Signal Processing Guskov et al
    1999
  • Cut and Paste Surface Editing Biermann et al
    2001

9
Related Work
  • Generative modelling Snyder 1992
  • Wires Singh and Fiume 1998
  • Poisson-based editing Yu et al 2004

10
Related Work
  • Teddy Igarashi et al 1999, 2001

11
Approach Overview
  • Select surface curves
  • Transform surface curves with Curve Analogies
  • Transform the surface
  • 2D sketch-based manipulation
  • Simple implementation

12
Curve Selection
  • Planar intersection curves
  • Parallel or rotating slices

13
Curve Selection
  • Planar intersection curves
  • Parallel or rotating slices
  • Silhouette curves

14
Generality Issues
  • Features controlled only on and along curves
  • Use orthogonal, intersecting sets of curves
  • Multiple passes

15
Curve Analogies
  • User sketches unfiltered, filtered curves
  • Identical parameterizations required
  • System iteratively copies offsets to target

16
Curve Analogies
  • Joint neighbourhood matching
  • Find best t with A(t) B(tcurr), A(t)
    B(tcurr)
  • Neighbourhoods must be aligned before comparison

17
Surface Transformation
  • Similar to Wires
  • Vertices near a curvetrack movement oftheir
    closest points onthe curve

18
Surface Transformation
  • Similar to Wires
  • Vertices near a curvetrack movement oftheir
    closest points onthe curve
  • Vertex movementinversely proportional to
    distance to curve

19
Surface Transformation
  • Similar to Wires
  • Vertices near a curvetrack movement oftheir
    closest points onthe curve
  • Vertex movementinversely proportional to
    distance to curve
  • Parallel local frames

20
Influence Radius
  • Radius of influence of each curve can be varied
  • Can also vary fall-off function

21
Influence Radius
  • Radius of influence of each curve can be varied
  • Can also vary fall-off function

22
Influence Radius
  • Radius of influence of each curve can be varied
  • Can also vary fall-off function

23
Multiple Curves
  • Vertices can be influencedby multiple curves
  • Candidate position from each influencing curve
  • Final position weighted average of candidates

24
Results
  • Curve Analogies
  • Dominate compute time
  • Can be difficult to control

25
Results
26
Results
27
Results
  • Harmonic fields Ni et al 2004

28
Future Directions
  • Better Curve Analogies
  • Avoid orientation flipping usingsurface
    information
  • Use intrinsic curveparameterization
    toaccelerate
  • Spatial influencesnear intersections

29
Future Directions
30
Future Directions
  • Poisson-based surface transformation
  • Can we use Image Analogies similarly?

31
Thanks
  • Funded in part by a grant from the NSF
    (CCR-0086084)
  • Software/source code at
  • http//graphics.cs.uiuc.edu/zelinka
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