Shape Analysis and Retrieval - PowerPoint PPT Presentation

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Shape Analysis and Retrieval

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Funk et al., SIGGRAPH 2004. Shape Histograms. Shape descriptor stores a histogram of how much surface resides at different bins in space ... – PowerPoint PPT presentation

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Title: Shape Analysis and Retrieval


1
Shape Analysis and Retrieval
  • Shape Histograms
  • Ankerst et al. 1999

Notes courtesy of Funk et al., SIGGRAPH 2004
2
Shape Histograms
  • Shape descriptor stores a histogram of how much
    surface resides at different bins in space

Model
Shape Histogram (Sectors Shells)
3
Boundary Voxel Representation
  • Represent a model as the (anti-aliased)
    rasterization of its surface into a regular grid
  • A voxel has value 1 (or area of intersection) if
    it intersects the boundary
  • A voxel has value 0 if it doesnt intersect

Model
Voxel Grid
4
Boundary Voxel Representation
  • Properties
  • Invertible
  • 3D array of information
  • Can be defined for any model

Point Clouds
Polygon Soups
Closed Meshes
Genus-0 Meshes
Shape Spectrum
5
Retrieval Results
6
Histogram Representations
  • Challenge
  • Histogram comparisons measure overlap, not
    proximity.

7
Histogram Representations
  • Solution
  • Quadratic distance form

8
Histogram Representations
  • Solution
  • Quadratic distance form
  • M is a symmetric matrix and can be expressed
    asO is a rotation and D is diagonal with
    positive entries.
  • Taking the square root

9
Histogram Representations
  • Solution
  • Quadratic distance form factors
  • If v(v1,,vn), we have
  • That is, M1/2(v) is just the convolution of v
    with some filter.

10
Convolving with a Gaussian
  • The value at a point is obtained by summing
    Gaussians distributed over the surface of the
    model.
  • Distributes the surface into adjacent bins
  • Blurs the model, loses high frequency information

Surface
Gaussian
Gaussian convolved surface
11
Gaussian EDT
  • The value at a point is obtained by summing the
    Gaussian of the closest point on the model
    surface.
  • Distributes the surface into adjacent bins
  • Maintains high-frequency information

max
Gaussian EDT
Surface
Gaussian
Kazhdan et al., 2003
12
Gaussian EDT
  • Properties
  • Invertible
  • 3D array of information
  • Can be defined for any model
  • Difference measures proximity between surfaces

Point Clouds
Polygon Soups
Closed Meshes
Genus-0 Meshes
Shape Spectrum
13
Retrieval Results
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