Lecture 9 : Point Set Processing - PowerPoint PPT Presentation

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Lecture 9 : Point Set Processing

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Title: Author: Bong-Soo Sohn Last modified by: bongbong Created Date: 1/26/2006 6:32:23 PM Document presentation format – PowerPoint PPT presentation

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Title: Lecture 9 : Point Set Processing


1
Lecture 9 Point Set Processing
Acknowledgement Prof. Amentas slides
2
Point Set (Point Cloud)
  • Often obtained from laser snanners

3
Building Information Modeling (BIM)
4
Human Body Shapes
5
Triangulations (Delaunay) Dual Diagrams
(Voronoi)
Union of Balls
  • Union of balls
  • Triangulation Dual

6
Data Structures for Point Set Data
  • Voronoi Diagram
  • Delaunay Triangulation
  • Medial Axis

7
Voronoi Diagram/Delaunay Triangulation
  • Refer to Prof. Vignerons slides

8
Medial Axis
  • A Transformation For Extracting New Descriptors
    of Shape
  • Locus of points equidistant from contour
  • Skeleton

9
Applications of medial axis
  • Shape matching
  • Animation
  • Computer Vision
  • Dimension reduction (Simplification)
  • Solid modeling

10
Definitions of medial axis
  • Locus of points equidistant from contour
  • Grass-fire, prairie-fire, wave-front collision
  • Locus of centers of maximal circles
  • Local maxima in distance transform
  • Result of topology preserving thinning

11
medial axisBlums equivalent definitions
12
Medial Axis
  • A set of points with more than one closest
    surface point

13
3D Medial Axis
  • A set of points with more than one closest
    surface point

14
Medial Axis
  • Maximal ball avoiding surface is a medial ball
  • Every solid is a union of balls

15
Relation to Voronoi
  • Voronoi balls approximate medial balls
  • For dense surface samples in 2D, all voronoi
    vertices lie near axis

16
Convergence
  • In 2D, set of Voronoi vertices converges to the
    medial axis as sampling density increases.

17
Discrete Union of Balls
  • Voronoi balls approximate the object and its
    complement.

18
2D Curve Reconstruction
  • Blue Delaunay edges reconstruct the curve, pink
    triangulate interior/exterior.
  • Many algorithms, with proofs, for coloring edges.

19
2D Curve Reconstruction
ltVoronoi Diagram of point set Sgt
  • Delaunay Triangulation of point set S
  • and voronoi vertices V
  • Black lines represent curve reconstruction

20
2D Medial Axis Reconstruction
  • Pink approximate medial axis.

21
3D Case
  • Different from 2D
  • In 3D, some Voronoi vertices are not near medial
    axis
  • Red voronoi cell of the blue point
  • Notice the red voronoi vertex that is far from
  • the medial axis

22
Union of Balls centered on voronoi vertices
  • 2D
  • 3D
  • Even when samples are
  • arbitrarily dense

23
Poles
  • Farthest voronoi vertices
  • p , p- (opposite sides)
  • Subset of voronoi vertices,
  • the poles, approximate
  • near medial axis

24
Union of balls centered on interior poles
25
3D surface reconstruction
  • Similar to 2D surface reconstruction, but use
    poles instead of entire voronoi vertices

26
Results Amenta 1998,2001
Laser range data, power crust, simplified
approximate medial axis
27
Shape Feature SegmentationDey 2003
  • Based on Voronoi Diagram and Delaunay
    Triangulation

28
Flow Field of Shape
29
Shape Feature Segmentation
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