2010 - alice.loria.fralice.loria.fr/publications/papers/2010/LPCVT/supplemental/LpCVT... · Lp...
Transcript of 2010 - alice.loria.fralice.loria.fr/publications/papers/2010/LPCVT/supplemental/LpCVT... · Lp...
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SIGGRAPH 2010
Lp Centroidal Voronoi Tesselations
Bruno Lévy and Yang Liu
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Overview
• 1. Motivations
• 2. Blowing Square Bubbles
• 3. Algorithm
• 4. Applications and Results
• 5. Conclusions and Future Work
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1. Motivations – Hex meshing
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1. Motivations – Why Hexes ?Tet Meshing
1. Fully Automated
2. Millions of elements in
minutes/seconds
3. Adequate for some analysis
4. Inaccurate for other Analysis
Hex Meshing
1. Partially Automated, some Manual
2. Millions of elements in
days/weeks/months
3. Preferred by some analysts for
solution quality
[Matt Staten] (Sandial Labs)
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2. Blowing Square Bubbles
p=2 p=4 p=8 ….
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2. Blowing Square Bubbles
Disclaimer:
This presentations contains live demos.Crashes may occur.
The presenter assumes no liability.
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3. Algorithm
F= ∫Vor(i)
2
dx(xi – x)i
Standard CVT:
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3. Algorithm
F= ∫Vor(i)
p
dxM(x) (xi – x)i p
F= ∫Vor(i)
2
dx(xi – x)i
Standard CVT:
Lp CVT:
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3. Algorithm
F= ∫Vor(i)
p
dxM(x) (xi – x)i p
Lp CVT:
Anisotropy, encodes desired orientation
Riemannian metric G = Mt M
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3. Algorithm
F= ∫Vor(i)
p
dxM(x) (xi – x)i p
Lp CVT:
Lp norm: || x ||p = xp + yp + zp
p= xp + yp + zpIf p is even: || x ||
p
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3. Algorithm
F= ∫Vor(i)
p
dxM(x) (xi – x)i p
Lp CVT:
Optimization with LBFGS (quasi-Newton)
For each iterate X(k):
Compute F(X(k)) and F(X(k))
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3. Algorithm F= ∫Vor(i)
p
dxM(x) (xi – x)i p
Computing F(X(k)) and F(X(k))
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3. Algorithm F= ∫Vor(i)
p
dxM(x) (xi – x)i p
Computing F(X(k)) and F(X(k))
xi
Vor(xi)
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3. Algorithm F= ∫Vor(i)
p
dxM(x) (xi – x)i p
Computing F(X(k)) and F(X(k))
Vor(xi)
clipped by
Domain.
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3. Algorithm F= ∫Vor(i)
p
dxM(x) (xi – x)i p
Computing F(X(k)) and F(X(k))
Computing the intersection between
a 3D Voronoi diagram and the interior
of a polygonal mesh - DEMO
An example in 3D
(cross-section)
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3. Algorithm F= ∫Vor(i)
p
dxM(x) (xi – x)i p
Computing F(X(k)) and F(X(k))
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3. Algorithm Computing F(X(k)) and F(X(k))
∫T
p
dxM(x) (xi – x)p
xi
C1
C2
Problem #1: FT(xi,C1,C2)
Integration
simplex
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3. Algorithm Computing F(X(k)) and F(X(k))
∫T
p
dxM(x) (xi – x)p
xi
C1
C2
Problem #1: FT(xi,C1,C2)
Problem #2: C1(xi, xj, xk)
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3. Algorithm
∫T
p
dxM(x) (xi – x)p
The formula is terrible…
* When in doubt, use brute force
* I’d rather write programs that write programs
than write programs
[Tom Duff, Bell Labs]
Programming Pearls John Bentley
Lp-CVT: the making of….
(not in the paper)
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3. Algorithm
∫T
p
dxM(x) (xi – x)p
template <class T> struct vec3g {
vec3g(T x_in, T y_in, T z_in) :
x(x_in), y(y_in), z(z_in) { }
T length2() const { return x*x+y*y+z*z ; }
T length() const { return sqrt(length()) ; }
T x,y,z ;
} ;
typedef vec3g<double> vec3 ;
typedef vec3g<Ginac::Expression> vec3s ;
Lp-CVT: the making of….
(not in the paper)
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3. AlgorithmLp-CVT: the making of….
Problem #1: FT(xi,C1,C2)
∫T
p
dxM(x) (xi – x)p
inline vec3s tri_point(
const vec3s& p1, const vec3s& p2, const vec3s& p3, const vec3s& p4,
const Expression& u, const Expression& v, const Expression& w
) {
Expression t = 1 - u - v - w ;
return u*p1 + v*p2 + w*p3 + t*p4 ;
}
inline Expression tri_dist(
const vec3s& p1, const vec3s& p2, const vec3s& p3, const vec3s& p4,
const Expression& u, const Expression& v, const Expression& w,
const vec3s& q
) {
return length_Lp(M, q - tri_point(p1,p2,p3,p4,u,v,w)) ;
}
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3. Algorithm
∫T
p
dxM(x) (xi – x)p
inline Expression LpCVT_energy_symbolic(
const vec3s& p1, const vec3s& p2, const vec3s& p3, const vec3s& p4
) {
symbol u("u"), v("v"), w("w") ;
Expression result =
tetra_volume(p1,p2,p3,p4) *
integ(u, 0, 1,
integ(v, 0, 1-u,
integ(w, 0, 1-u-v,
tri_dist(p1,p2,p3,p4,u,v,w,p1)
)
)
) ;
return result ;
}
Lp-CVT: the making of….
Problem #1: FT(xi,C1,C2)
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3. AlgorithmLp-CVT: the making of….
Problem #2: C(xi, xj, xk)
pi
Intersections of bisectorsvec3g<T> three_planes_intersection(
const Plane<T>& P1,
const Plane<T>& P2, const Plane<T>& P3
) {
T b00, b01, b02, b10, b11, b12, b20, b21, b22 ;
// Note: b is transposed
comatrix3x3(
P1.a, P1.b, P1.c,
P2.a, P2.b, P2.c,
P3.a, P3.b, P3.c,
b00, b10, b20,
b01, b11, b21,
b02, b12, b22
) ;
return -T(1) / det3x3(
P1.a, P1.b, P1.c,
P2.a, P2.b, P2.c,
P3.a, P3.b, P3.c
) * vec3g<T>(
P1.d * b00 + P2.d * b01 + P3.d * b02,
P1.d * b10 + P2.d * b11 + P3.d * b12,
P1.d * b20 + P2.d * b21 + P3.d * b22
) ;
}
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3. AlgorithmLp-CVT: the making of….
Assembling F and F
F(pi,p1,p2)
C(xi,xj,xk) C(xi,xl,xm)xi
FunctionCompose class
+ chain rule to compute derivatives
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3. AlgorithmLp-CVT: the making of….
It works ! (the 2D demo is done with this « symbolic » code), but too slow for 3D
Math-O-Matic
∫T
p
dxM(x) (xi – x)p
Written in C++ + Ginac
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3. AlgorithmLp-CVT: the making of….
It works ! (the 2D demo is done with this « symbolic » code), but too slow for 3D
Math-O-Matic
∫T
p
dxM(x) (xi – x)p
Written in C++ + Ginac,
Instanciation with Exp class.
void eval_F_Lp(
unsigned int n,
const double* X,
double& F_Lp,
double* grad_F_Lp
) ;
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3. Algorithm
Can we do better ?
Do not let the computer think for us,
We need to crank the algebra…
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3. Algorithm : chalk and board
univariate, 1D version
can we have a nD version on simplices ?
[Lasserre and Avrachenkov 2000]
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3. Algorithm : chalk and boardHomogeneous polynomial in polar form H():
example: x4 = H(x,x,x,x)
H(x,x,x,x) = x1 * x2 * x3 * x4
replace degree q with multilinear form of q variables
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3. Algorithm : chalk and board
[Lasserre and Avrachenkov 2000]
Homogeneous polynomial in polar form H():
example: x4 = H(x,x,x,x)
H(x,x,x,x) = x1 * x2 * x3 * x4
replace degree q with multilinear form of q variables
nD version (n: dimension; q: degree of the polynomial)
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3. Algorithm : chalk and board
p1
p2
p3
x1
C3
C2
C4
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3. Algorithm : chalk and board
∫p
dx
T(x1,C2,C3,C4)
x - x1F=
p1
p2
p3
x1
C3
C2
C4
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3. Algorithm : chalk and board
∫p
dx
T(x1,C2,C3,C4)
x - x1F=
p1
p2
p3
x1
C3
C2
C4
∫p
dx
T(0,C2-x1,C3-x1,C4-x1)
x F =
Translate x1 at origin :
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3. Algorithm : chalk and board
nD version (n: dimension; q: degree of the polynomial)
∫p
dx
T(0,C2-x1,C3-x1,C4-x1)
x F =
p
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3. Algorithm : chalk and board
nD version (n: dimension; q: degree of the polynomial)
∫p
dx
T(0,C2-x1,C3-x1,C4-x1)
x F =
H(x,x) = xp H(x1,…,xp) = x1*…*xp
U1 = C2-x1;
U2 = C3-x1;
U3 = C4-x1U1
U2
U3p
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3. Algorithm : chalk and board
nD version (n: dimension; q: degree of the polynomial)
∫p
dx
T(0,C2-x1,C3-x1,C4-x1)
x F =
H(x,x) = xp H(x1,…,xp) = x1*…*xp
U1 = C2-x1;
U2 = C3-x1;
U3 = C4-x1U1
U2
U3p
F = 10 p!
Vol(T) ∑ (Ui1* Ui2* Ui3 ...* Uip)
i1, i2, ... ip in (1,2,3)
This solves problem #1
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3. Algorithm : chalk and board
nD version (n: dimension; q: degree of the polynomial)
∫p
dx
T(0,C2-x1,C3-x1,C4-x1)
x F =
H(x,x) = xp H(x1,…,xp) = x1*…*xp
U1 = C2-x1;
U2 = C3-x1;
U3 = C4-x1U1
U2
U3p
F = 10 p!
Vol(T) ∑ (Ui1* Ui2* Ui3 ...* Uip)
i1, i2, ... ip in (1,2,3)
This solves problem #1
Problem #2
[Minka] Matrix computation
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3. Algorithm : chalk and boardProblem #2 : circumcenters and their derivatives
[Minka] Matrix computation
C
x1x2
x3
x0
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3. Algorithm : chalk and boardProblem #2 : circumcenters and their derivatives
[Minka] Matrix computation
C
x1x2
x3
x0
C = intersection of 3 bisector planes
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3. Algorithm : chalk and boardProblem #2 : circumcenters and their derivatives
[Minka] Matrix computation
C
x1x2
x3
x0
C = intersection of 3 bisector planes
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3. Algorithm : chalk and boardProblem #2 : circumcenters and their derivatives
[Minka] Matrix computation
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3. Algorithm : chalk and boardProblem #2 : circumcenters and their derivatives
[Minka] Matrix computation
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3. Algorithm : chalk and boardProblem #2 : circumcenters and their derivatives
[Minka] Matrix computation
C
x1x2
x3
x0
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3. Algorithm : chalk and board
C
x1x2
x3
x0
Can the results bereproduced by a grad
student ?
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3. Algorithm : chalk and board
C
x1x2
x3
x4
Source code on the DVD
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4. Applications and Results
p = 2
M(x) = ppal dir.
of curvature.
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4. Applications and results
p = 2
M(x) = Normal
anisotropy.
Feature-sensitive meshing
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4. Applications and results
p = 2
M(x) = Normal
anisotropy.
Feature-sensitive meshing
CSG-Remeshing - DEMO
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4. Applications and results
p = 8
M(x) = ppal dir.
of curvature.
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4. Applications and results
+ many other examples in paper
and supplemental material.
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4. Applications and results
Demo
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5. Future Work
To L and beyond !
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5. Future Work
•
CVT for line segment and graphs
(Accepted pending rev.)
L CVT, structured meshing
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Aknowledgements
• Bytes : CGAL (Delaunay triangulation)
• Triangles: AIM@Shape, Digital Michelangelo
• Euros : European Research Council
GOODSHAPE ERC-StG-205693
Rhaleb Zayer, Wenping Wang, Jean-Francois Remacle,
Nicolas Saugnier, DongMing Yan, Loic Maréchal, Pierre Alliez,
Tamal Dey, Pierre Alliez, David Bommes, Leif Kobbelt