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Analysis of Subdivision Surfaces at Extraordinary Vertices. Dr. Scott Schaefer. Structure of Subdivision Surfaces. Structure of Subdivision Surfaces. Structure of Subdivision Surfaces. Structure of Subdivision Surfaces. Structure of Subdivision Surfaces. Structure of Subdivision Surfaces.
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Analysis of Subdivision Surfaces at Extraordinary Vertices Dr. Scott Schaefer
Structure of Subdivision Surfaces • If ordinary case is smooth, then obviously entire surface is smooth except possibly at extraordinary vertices
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
Subdivision Matrices • Encode local subdivision rules around extraordinary vertex
Subdivision Matrix Example • Repeated multiplication by S performs subdivision locally • Only need to analyze S to determine smoothness of the subdivision surface
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
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
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
Structure of Subdivision Matrices Circulant matrix
Circulant Matrices • Matrix whose rows are horizontal shifts of a single row
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
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
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
Block-Circulant Matrices • Matrix composed of circulant matrices
Block-Circulant Matrices • Matrix composed of circulant matrices
Block-Circulant Matrices • Matrix composed of circulant matrices
Eigenvalues/vectors ofBlock-Circulant Matrices • Find eigenvalues/vectors of block matrix eigenvectors eigenvalues inverse of eigenvectors
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
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
Example: Loop Subdivision Some parts of the matrix are not circulant
Example: Loop Subdivision • Eigenvectors/values for block-circulant portion are eigenvectors/values for entire matrix except at j=0
Example: Loop Subdivision • Subdominant eigenvalue is • Corresponding eigenvector is
Example: Loop Subdivision • Subdominant eigenvalue is • Corresponding eigenvector is • Plot real/imaginary parts to create char map
S Application: Exact Evaluation
Application: Exact Evaluation • Subdivide until x is in ordinary region
Application: Exact Evaluation • Subdivide until x is in ordinary region
Application: Exact Evaluation • Subdivide until x is in ordinary region
Application: Exact Evaluation • Subdivide until x is in ordinary region • Extract B-spline control points and evaluate at x
Application: Exact Evaluation • Subdivide until x is in ordinary region • Extract B-spline control points and evaluate at x