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Dr' Scott Schaefer

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Title: Dr' Scott Schaefer


1
Analysis of Subdivision Surfaces at
Extraordinary Vertices
  • Dr. Scott Schaefer

2
Structure of Subdivision Surfaces
3
Structure of Subdivision Surfaces
4
Structure of Subdivision Surfaces
5
Structure of Subdivision Surfaces
6
Structure of Subdivision Surfaces
7
Structure of Subdivision Surfaces
8
Structure of Subdivision Surfaces
9
Structure of Subdivision Surfaces
10
Structure of Subdivision Surfaces
  • If ordinary case is smooth, then obviously entire
    surface is smooth except possibly at
    extraordinary vertices

11
Smoothness of Surfaces
  • A surface is a Ck manifold if locally the surface
    is the graph of a Ck function
  • Must develop a local parameterization around
    extraordinary vertices to analyze smoothness

12
Subdivision Matrices
  • Encode local subdivision rules around
    extraordinary vertex

13
Subdivision Matrix Example
14
Subdivision Matrix Example
  • Repeated multiplication by S performs subdivision
    locally
  • Only need to analyze S to determine smoothness of
    the subdivision surface

15
Smoothness at Extraordinary Vertices
  • Reif showed that it is necessary for the
    subdivision matrix S to have eigenvalues of the
    form where for the
    surface to be C1 at the extraordinary vertex
  • A sufficient condition for C1 smoothness is that
    the characteristic map must be regular and
    injective

16
The Characteristic Map
  • Let the eigenvalues of S be of the form
  • where .
  • The eigenvectors associated with provide a
    local parameterization around the extraordinary
    vertex

17
The Characteristic Map
18
The Characteristic Map
19
The Characteristic Map
20
The Characteristic Map
21
Analyzing Arbitrary Valence
  • Matrices become very large, very quickly
  • Must analyze every valence independently
  • Need tools for somehow analyzing
    eigenvalues/vectors of arbitrary valence easily

22
Structure of Subdivision Matrices
23
Structure of Subdivision Matrices
Circulant matrix
24
Circulant Matrices
  • Matrix whose rows are horizontal shifts of a
    single row

25
Eigenvalues/vectors of Circulant Matrices
  • Given an circulant matrix with rows
    associated with c(x), its eigenvalues are of the
    form and has eigenvectors
  • where and

26
Eigenvalues/vectors of Circulant Matrices
  • Given an circulant matrix with rows
    associated with c(x), its eigenvalues are of the
    form and has eigenvectors
  • where and

27
Eigenvalues/vectors of Circulant Matrices
  • Given an circulant matrix with rows
    associated with c(x), its eigenvalues are of the
    form and has eigenvectors
  • where and

28
Block-Circulant Matrices
  • Matrix composed of circulant matrices

29
Block-Circulant Matrices
  • Matrix composed of circulant matrices

30
Block-Circulant Matrices
  • Matrix composed of circulant matrices

31
Eigenvalues/vectors ofBlock-Circulant Matrices
  • Find eigenvalues/vectors of block matrix

eigenvectors
eigenvalues
inverse of eigenvectors
32
Eigenvalues/vectors ofBlock-Circulant Matrices
  • Find eigenvalues/vectors of block matrix
  • Eigenvalues of block matrix are eigenvalues of
    expanded matrix evaluated at

eigenvectors
eigenvalues
inverse of eigenvectors
33
Eigenvalues/vectors ofBlock-Circulant Matrices
  • Find eigenvalues/vectors of block matrix
  • Eigenvalues of block matrix are eigenvalues of
    expanded matrix evaluated at
  • Eigenvectors of block matrix are multiples of
  • times eigenvectors of block
    matrix

eigenvectors
eigenvalues
inverse of eigenvectors
34
Eigenvalues/vectors ofBlock-Circulant Matrices
35
Eigenvalues/vectors ofBlock-Circulant Matrices
36
Example Loop Subdivision
37
Example Loop Subdivision
Some parts of the matrix are not circulant
38
Example Loop Subdivision
  • Eigenvectors/values for block-circulant portion
    are eigenvectors/values for entire matrix except
    at j0

39
Example Loop Subdivision
40
Example Loop Subdivision
41
Example Loop Subdivision
42
Example Loop Subdivision
  • Subdominant eigenvalue is
  • Corresponding eigenvector is

43
Example Loop Subdivision
  • Subdominant eigenvalue is
  • Corresponding eigenvector is
  • Plot real/imaginary parts to create char map

44
ExampleLoop Subdivision
45
Application Exact Evaluation
46
Application Exact Evaluation
  • Subdivide until x is in
  • ordinary region

47
Application Exact Evaluation
  • Subdivide until x is in
  • ordinary region

48
Application Exact Evaluation
  • Subdivide until x is in
  • ordinary region

49
Application Exact Evaluation
  • Subdivide until x is in
  • ordinary region
  • Extract B-spline control
  • points and evaluate at x

50
Application Exact Evaluation
  • Subdivide until x is in
  • ordinary region
  • Extract B-spline control
  • points and evaluate at x
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