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![Page 1: Implicit Surface Modeling - Zhejiang · PDF fileImplicit Surface Modeling Hongxin Zhang and Jieqing Feng 2007-01-04 State Key Lab of CAD&CG Zhejiang University](https://reader030.vdocuments.mx/reader030/viewer/2022012902/5a9dcdd37f8b9ae0108bbe00/html5/thumbnails/1.jpg)
Implicit Surface Modeling
Hongxin Zhang and Jieqing Feng
2007-01-04
State Key Lab of CAD&CGZhejiang University
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Contents
• Introduction of Implicit Surface Modeling• Implicit Surface Modeling for Computer
Graphics and Animation: Field Function Defined Implicit Surface
• Quadric Surfaces• Download Course
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Introduction of Implicit Surface Modeling
• What is implicit surface?• Comparison: implicit v.s. parametric
surfaces• Implicit methods for graphics and
animation• Implicit methods for CAD/CAM• Other topics in implicit modeling
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What is implicit surface?
• Implicit surfaces are two-dimensional, geometric shapes that exist in three dimensional space.
Defined in R3: 2-D manifold:
A surface embedded in R3
Infinitesimal neighborhood around any point on the surface is topologically equivalent (‘ locally diffeomorphic’) to a disk.
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What is implicit surface?
2D manifold can be bounded (or closed): sphereUnbounded: plane
A manifold with boundary: topologically equivalent to either a disk or a half-disk locally.Nonmanifold
NonmanifoldManifold Manifold with boundary
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What is implicit surface?
Manifold or not? Eule-Poincaré formula
v-e+f=2-2h
v: number of verticese: number of edgesf: number of facesh: number of holes
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Examples of implicit surfaces
Metaball Skeleton Surface and Metaball
Convolution Surface
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Examples of implicit surfaces
Quadric Surface Compactly Supported Radial Basis Functions
A-Patch
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Definition of implicit surface
• Definition{p=(x,y,z): f(p)=0, p∈R3}
Implicit function f : three classes of specification (definition)
Discrete sampling: a set of points on or within an objectMathematical function: one or more equations are used to compute the coordinates of points on or within an objectProcedural methods: an algorithmic process computes points on or within an object
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Algebraic Function
• Algebraic surface: when f is algebraic function, i.e., polynomial function
The coefficients are not uniquef=ax+by+cz=0
a=b=c=1a=b=c=1/√3
Algebraic distance: The value of f(p) is the approximation of distance from p to the algebraic surface f=0
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Transcendental Function
• Transcendental FunctionTrigonometric, exponential, logarithmic, hyperbolic functions, etc.Approximated by convergent power series: Taylor series
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Definition of implicit surface
• Regular point p on the surface∇f (p) =(∂f/∂x, ∂f/∂y, ∂f/∂z) ≠ 0
For cone, 0 is not the regular value for f
The cone f=-x2+y2+z2 is regular with the exception of a singularity at the origin (0,0,0).
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Mathematical Foundation
• Implicit Function Theorem:if 0 a regular value of continuous function f(p), the implicit surface f-1(0) is a two-dimensional manifold
• Jordan-Brouwer Separation TheoremA 2D manifold separates R3 into surface itself and two connected open sets: an infinite(finite) `outside' and a finite(infinite) ‘inside'.
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Mathematical Foundation
f (x,y,z) = x2+y2+z2f (x,y,z) -1=x2+y2+z2-1
f > 0 outside
f = 0 surfacef < 0 inside
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Implicit v.s. Parametric Surfaces
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Complex Surface Modeling
Complex surface constructed by smoothly joined B-spline surface
patches Complex surface constructed by convolution surface method
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Surfaces Intersection
Parametric Surface Intersection Implicit Surface Intersection
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Tessellation
Up: tessellation of implicit surface
Bottom: tessellation of NURBS surface
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Blending or rounding
Left: Blending by using parametric surface
Right: Blending by using implicit surface
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Texture mapping
Texture mapping for NURBS surface Texture mapping for implicit surface
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Solid Modeling
Solid Modeling via Implicit SurfaceSolid Modeling via NURBS Surface
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Implicit v.s. Parametric Surfaces
• Implicitization:
• Parameterization
Parametric representation
Implicit representation
Implicit representation
Parametric representation
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About conversions
• ImplicitizationAny rational parametric surface can be implictized by elimination of parameters in the parametric formImplicitization is often computational demandingThe degree of implicit form is higher than its parametric form, the implicit representation of
A parametric triangular patch of degree n is degree n2
A tensor product surface of degree m by n is degree 2mnThe number of terms in algebraic surface of degree n is (bicubic patch is degree 18, with 1330 terms!)Approximated implicitization
23Cn
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About conversions
• Parameterization: not always possible Algebraic surfaces of fourth and higher degree cannot be parameterized by rational functionsParameterization is always possible for non-degenerate quadrics and for cubics that have a singular point.
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Example:sphere
• Trigonometric: f(α,β)=(cosαcosβ, cosαsinβ, sinα)
α∈[0,π], β∈[0,2π]• Rational:
x=4st, y=2t(1-s2), z=(1-t2)(1+s2), w=(1+t2)(1+s2)
• Implicit:
f(x,y,z)=x2+y2+z2-1
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Example: sphere
• Points on the parametrically defined sphere are readily found by substitution of α and β into the equations for x, y, and z(similarly for s and t).
• The mapping from parametric space to geometric space is convenient.
• There is no obvious mapping for implicit form!
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Implicit methods for graphics and animation
• Blobby (metaball, soft objects)• Implicit surface defined by skeletons
Distance surfaceConvolution surface
• Variational Implicit Surfaces• Level-Set Methods• Procedural Models• Animation applications
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Blobby (metaball, soft objects)
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Implicit surface defined by skeletons
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Variational Implicit Surfaces
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Level-Set Surface Models
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Procedural Models
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Reconstruction
The polygonal bunny model was approximated by metaballs.
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Animation applications
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Implicit methods for CAD/CAM
• Quadric surface • Algebraic surface patches
A-patchTensor-product algebraic surface patches
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Quadric Surface
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A-patch: Algebraic Surface Patch
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A-patch: Algebraic Surface Patch
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Tensor-product algebraic surface patches
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Tensor-product algebraic surface patches
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Other Topics in Implicit Modeling
• Functional representation• Visualizing implicit surfaces• Animation by using implicit models• Texture mapping
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Functional Representation (F-rep)
• F-rep: denfines a whole geometric object by a single real continuous function of several variables as F(X)≥0
At least C0 continuousF: a formula or an evaluation procedureF-rep: combines classic implicits, skeleton based implicits, set-theoretic solids, sweeps, volumetric objects, parametric and procedural models
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Functional Representation (F-rep)
• Set-theoretic operations• Blending set-theoretic
operations• Offsetting• Cartesian product• Bijective mapping• Metamorphosis
• Relations• Sweeping by a moving
solid • Deformation with
algebraic sums• Three-dimensional
texture modeling• Interaction
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F-rep: examples
Moving solid
Artistic shape modeling using real functions
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F-rep: hairs
Using real functions with application to hair modeling
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Visualizing implicit surfaces
• Polygonization: Generation of polygons from implicit surface or volume data
UniformAdaptive
• Ray tracingClassicalSphere tracing
• Particle system
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Uniform Polygonization
A sphere approximated from depths 1 through 5.
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Adaptive Polygonization
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Polygonization of non-manifold
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Classic Ray Tracing
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Sphere tracing
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Sphere tracing
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Particle system: display and control
http://graphics.cs.uiuc.edu/projects/surface/
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Field Function Defined Implicit Surface
• Field Function in 3D• Simple Control Primitives: point etc.
Blobby MoleculesMetaballSoft ObjectsDiscussion and Extensions
• Skeletal PrimitivesDistance surfaceConvolution surface
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Field Function in 3D
• Consider implicit surfaceD(x,y,z)-Iso=0
D is called scalar field functionDistance field is one of good choice
Distance to a Curve: 3 and 9 linear segments
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Example of Distance Field
• Consider function D(r)=1/r2 , control points in 3D space, where r is the distance to one control points
• The total field strength at any point in space is the sum of the field strengths due to each control point
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Example of Distance Field
• Changing control points as line segments
Simple summation of distance fields will result in bulge!
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Blobby Molecules by Blinn
• Second Graphics Fellow at Microsoft
• 1983 -- The first Siggraph Computer Graphics AchievementAward for work in lighting and surface modeling techniques.
• 1989 -- IEEE Outstanding Contribution Award for Jim Blinn'scornerJim Blinn
http://research.microsoft.com/users/blinn/
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Blobby Molecules
• Hydrogen atoms electron density fields (Gaussian Distribution)
"b" : standard deviation of Gaussian curve "a" : height of Gaussian Curve“r” : the distance to atom center, r≥0
2
( ) brD r ae−=
2D Gaussian Function 1D Gaussian Function
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Multiple Blobby Molecules
• The overall density at a given point for multiple atoms is summation of individual ones:
The “blobbiness” of a model can be controlled by adjusting the parameters ai and bi.
ai is weight/strength of ith blobby moleculebi is influence radius of ith blobby molecule
The implicit surface is defined as all points where the density is equal to some threshold value Iso.
2
( ) ib ri
i
D p a e Iso−= =∑
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Examples of Blobby Models
![Page 62: Implicit Surface Modeling - Zhejiang · PDF fileImplicit Surface Modeling Hongxin Zhang and Jieqing Feng 2007-01-04 State Key Lab of CAD&CG Zhejiang University](https://reader030.vdocuments.mx/reader030/viewer/2022012902/5a9dcdd37f8b9ae0108bbe00/html5/thumbnails/62.jpg)
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Blobby Molecules
• Disadvantages of Blobby Molecules Exponential distribution of density is Global
Computationally expensive!Blinn: Cut off after r >R
R
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Metaball by Nishimura
• Nishimura at Osaka University in Japan proposed Metaball in 1983 (Almost same with Blinn)
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Metaball by Nishimura
• Piecewise quadrics to approximate the Gaussian function
"b" : Influence radius of metaball "a" : weight of metaball “r” : the distance to metaball center, r≥0
2
2
2
31 0 / 3
3( ) 1 / 32
0
ra r bb
a rD r b r bb
r b
⎧ ⎛ ⎞− ≤ ≤⎪ ⎜ ⎟
⎝ ⎠⎪⎪⎪ ⎛ ⎞= − ≤ ≤⎨ ⎜ ⎟
⎝ ⎠⎪⎪ ≥⎪
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Metaball Systems
• The system is composed of several metaball
Each metaball has its own parameters (ai, bi)Fusion effects
( ) ( )ii
D p D p Iso= =∑
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Examples of Metaballs
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Metaball
• AdvantagesField function is locally defined in [0,b]Fast ray and metaball intersection computation!
• DisadvantageDistance r: square root , expensive
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Soft Object by Wyvill Brothers
• Soft objects is proposed by Wyvills in Canada and New Zealand: truncated Taylor expansion series of exponential function
Geoff WyvillBrian Wyvill
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Field Function for Soft Object
• Definition
The function has following propertiesD(0)=1, D(b)=0, D(b/2)=0.5, C′(0)=C′(b)=0
The volume bounded by D(r)<m is one half of that bounded by D(r)<m/2
6 4 2
6 4 2
4 17 221 ( ) 9 9 9
0
r r ra r bD r b b b
r b
⎧ ⎛ ⎞− + − ≤⎪ ⎜ ⎟=⎨ ⎝ ⎠
⎪ >⎩
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Examples of Soft Objects
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Examples of Soft Objects
Two blend soft objects with different threshold: 84, 44, 24, 11
25 balls, threshold is 0.5 Trains modeled by soft objects
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Soft Object
• AdvantagesOnly square term of the distance r, square root computation is removed!Finite extent of each ballComputational costs:
Blobby >> Metaball > Soft object
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Discussions
• The functions described here guarantee a continuously and smoothly changing surface
• Comparison of four field functions
• The blending function can be designed freely!
rt
t
rmax
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Extensions
• Minus primitives: set weight negative
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Applications of Metaball
Shape approximation and representation by metaballs
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Skeletal Primitives
• Disadvantage of point primitives: flat surfaces can only be approximated.
Evenly spaced grid of metaballs(16): threshold is 1.66 or 0.5
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Skeletal Primitives
• The use of complex skeletons is one possible solution to this problem.
Point can be replace as lines, polygons, curves, surfaces , volumes and any other complex geometric skeletonsThe shape of a primitive follows the shape of its skeletons
• Two ApproachesDistance surfacesConvolution Surfaces
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Examples of Skeletal Primitives
skeletons
contour line drawing
skeletons
ray traced image
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Examples of Skeletal Primitives
Complex skeletons: ellipsoid, sphere, line segments, points
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Distance surface
• A distance surface is a surface that is defined by distance to some set of base skeleton elements
Union of skeletons: Distance surface to the union of skeletonsUnion of primitive surfaces: Boolean operation Blending of primitive surfaces: Algebraic blending
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Union of Skeletons
• Definition
S is the skeleton sets is the point on one of the skeletonmax: maximum field value, nearest point on the skeletonField function can be specified as before, not restricted as exponential function
2
( , ) max exp2s S
s pf S p ∈
⎛ ⎞−= −⎜ ⎟⎜ ⎟
⎝ ⎠
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About Union of Skeletons
• Distance surface is rounded when skeleton is convex.• Distance surface is tangent discontinuous and exhibits a
crease when the skeleton is concave
Left: curve shown as dashed and distance shown as greyscale intensitymiddle and right: curve approximated by three and nine segments
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01/04/2007 State Key Lab of CAD&CG 83
Union of Distance Surfaces
• Union of distance surface is defined as weighted union of each primitive surface
• Definition
ci: weight, positive or negativeFi: field function as beforeri: the distance from p to the nearest point on the i-th skeleton.
( ) ( )total i i iiF p c F r=∑
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About Union of Distance Surfaces
• Simple union of distance surfaces will produce bulges and creases may area where the skeletons meet.
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01/04/2007 State Key Lab of CAD&CG 85
Algebraic Blends of Primitives
• To eliminate creases or bulge , the primitive volumes (“metaball ”) must form a blend, rather than a union.
• What is blending: smooth transition along common boundary among several primitives
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Blending Functions (1)
• Super-elliptical Blending
P1, P2 are algebraic distances to skeletal elements 1 and 2, usually C1 continuousr1 and r2 are the ranges of influence for primitives P1 and P2
[x]+ is max (0, x), and t is the ‘thumbweight.’
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Example of Blending Functions (1)
Super-elliptical Blending of sphere and cylinder primitives (t=3)
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Example of Blending Functions (1)
Super-Elliptic Blend of Two Cylinders
There is a bulge where the cylinders intersect.
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Blending Functions (2)
• Improved Super-elliptical Blending
θ: the angle between the gradients of the two primitives at a point p:The influence range is diminished according to θ
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01/04/2007 State Key Lab of CAD&CG 90
Blending Functions (2)
θ = 0 the range is fully diminished and the simple union of the primitives resultsθ = 90°(concave condition), the range is undiminished, and a blend occurs. To avoid enlarging the primitive ranges, cos(θ) must be nonnegative
simple union bulging blend use of cos use of nonnegative cos
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01/04/2007 State Key Lab of CAD&CG 91
Blending Functions (3)
• Super-elliptical blend is extended to k primitives:
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Convolution Surface
• A bulge-free implicit blend technique
• The convolution surface treats a skeleton S as a set of points, each of which contributes to the implicit surface function according to its distance to p.
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Convolution Surface
• Blobby systems by Blinn
where si is a point on the skeleton, c is threshold (constant)
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Convolution Surface
• If S = {si} is a set of infinitesimally spaced points, f can be expressed as an integral:
where u ranges over all points on the skeleton. It defines a convolution surfaceGaussian function is a 3D filter/kernel
• S = {si} can be any skeletons: point, line, curve, surface, volumes etc.
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01/04/2007 State Key Lab of CAD&CG 95
About Convolution Surface
• The convolution has been applied extensively in the processing of 1D audio signal, 2D image, 3D volume image.
• The convolution scaled the frequency components of the signal via filter(kernel)
Low-pass filter: smoothing effect, e.g., Gaussian kernel High-pass filter: enhance detail effect
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Gaussian Kernels
Gaussian Kernels: left: one-dimensional, right: two-dimensional
Infinite Sum is a Convolution
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About Convolution Surface
• The convolution is a linear operator:
It is property of superpositionThe sum of the convolutions of any division of a skeleton is identically equal to the single convolution of the entire skeleton
• The convolution surface is a smooth shape without introducing bulges.
1 2 1 2( )h s s h s h s⊗ + = ⊗ + ⊗
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Illustration of Superposition
The superposition Property: The two line segment are brought together (left); sum of convolutions of the two segments (right), convolution of single segment (bottom)
Two Segments Convolved with the Gaussian Kernel
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01/04/2007 State Key Lab of CAD&CG 99
About Convolution Surface
• Along convex portions of the skeleton the surface mimics the union operator
• Along concave portions, the surface yields a blend.• For isolated convex skeletons, such as triangles or
segments, convolution produces surfaces of similar shape to distance surfaces.
• For complex skeletons, however, convolution yields crease-free surfaces with adjacent primitives blending without seam or bulge.
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01/04/2007 State Key Lab of CAD&CG 100
Gaussian kernel
• For standard Gaussian kernel:
A signal modified by such a kernel will maintain its original energy!
2
21 12
x
e dxπ
∞ −
−∞=∫
Convolution of a box with unit-integral kernel
1
1/2
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01/04/2007 State Key Lab of CAD&CG 101
Energy Discussion in Convolution
• Because the Gaussian is symmetric, the convolution equals ½ where the box function undergoes transitions
For an iso-surface contour level of ½, the convolution surface will pass through the endpoints of skeletal segments and through the edges of skeletal polygons.
• A kernel with integral less (greater) than one would attenuate (amplify) a signal
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01/04/2007 State Key Lab of CAD&CG 102
Gaussian kernel
• Advatnages of Gaussian KernelC∞ SmoothUnit integral Separable
• Disadvantages of Gaussian KernelGlobally Defined on the R1,2,3
Cannot be analytical integrated, only numerically approximated
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Examples of Convolution Surfaces
Two Segments Convolved with the Gaussian Kernel
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Examples of Convolution Surfaces
Threshold=1.0, 0.75, 0.5, 0.35
Line segment and arc skeletons
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Examples of Convolution Surfaces
Convolution Surface: Hand Crafted by Jules Bloomenthal
Convolution Surface
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Other kernels: Sinc Kernel
• Sinc kernel is : sin(πx)/πx.
The sinc is the ideal low-pass filter: its Fourier transform is the box function.Cutoff frequency effect
The Sinc Kernel
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Other kernels: Sinc Kernel
Problem with sinc kernel: none monotonically
• Monotonicity of the kernel is a necessary property for a satisfactory convolution surface
Ringing of the filter may introduce a spurious contour
Convolution with Gaussian (left) and Sinc (right)
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Other kernels: B-spline Kernels
• B-spline kernel has similar shape with Gaussian
hB-spline(0)=2/3, hB-spline(0.72235)≈1/2The support of kernel is 2The integral of B-Spline kernel is 1, not separable
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Other kernels: Wyvill Kernels
• Wyvill kernel also has similar shape with Gaussian
hWyvill(x) = (9-4x6+17x4-22x2)/9.After scale: hWyvill(0)=1, hWyvill(1)=1/2The integral of Wyvill kernel is 1The support of kernel is 1Not separable
Wyvill kernel (red)
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Other kernels: Modified WyvillKernels
• Modified Wyvill kernel also has similar shape with Gaussian
hNewWyvill(x) = (1-x2)3.After scale: hWyvill(0)=1The integral of Modified Wyvill kernel is 1The support of kernel is 1Not separable
Modified Wyvill kernel (blue)
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Compare the different kernels
Comparison of Filter Kernels after scaleupper (in black): the Gaussian kernel, e-0.69314715x2
middle (in red): the B-spline kernel, (1.5)hBspline(0.72235x)lower (in blue): the Wyvill kernel, hWyvill(0.5x)
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Computation of Convolution
• The Gaussian is separable and spherically symmetric
Integration by part!• B-spline and Wyvill kernel is not separable
summation of point source termsthe product of integration and distance filters.
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Computation of Convolution
Approximations to B-Spline Convolutionleft: summation of point sourcesright: product of filters
Approximations to Wyvill Convolutionleft: summation of point sourcesright: product of filters
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Computation of Convolution
Gaussian Convolution approximation for 3, 7, and 15 Segments (left) or Points (right)
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Ramification Modeling
A Two-Ramiform with Constant Radii
A Trifurcated Ramiform
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Please Enjoy More Examples of Convolution Surface
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Snowflake
Please Enjoy More Examples of Convolution Surface
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Potted plant
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Maple tree
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A gourd shape
Please Enjoy More Examples of Convolution Surface
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A dinosaur
Please Enjoy More Examples of Convolution Surface
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An cartoon enforcer
Please Enjoy More Examples of Convolution Surface
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Quadric Surfaces
• Basics of Quadric Surfaces• Properties of Quadric Surfaces• Representation of Quadric Surfaces• Applications of Quadric Surfaces
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Basics of Quadric Surfaces
• A general quadric surface isAx2 + By2 + Cz2 + 2Dxy + 2Exz + 2Fyz +2Gx +
2Hy + 2Jz + K = 0• Its matrix representation
{x | F(x) = xTQx = 0}where
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Basics of Quadric Surfaces
• There are nine types of general quadrics according coefficients of this algebraic equation
EllipsoidElliptic coneCylinder (elliptic, parabolic, hyperbolic)Hyperboloid (of 1 sheet, of 2 sheets)Paraboloid (elliptic, hyperbolic)
• Degenerated cases point, plane, parallel planes,
• Invalid shapes imaginary quadric, intersecting imaginary planes, imaginary parallel planes
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Sketches of General Quadric Surfaces
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Natural Quadrics
• Natural Quadrics: subset of general sphere (special case of ellipsoid) right circular cone (special case of elliptic cone)right circular cylinder (special case of elliptic cylinder)Planes
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Natural Quadrics
• Natural quadrics are by far the most popular set of quadric: Prismatic Solid
Mechanical CAD domains
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Quadric Surface Patches
• Pieced together with tangent plane (G1) continuity to create free-form shapes
Some complex free-form solids modeled with quadric algebraic patches: (a) a genus five solid with 2,400 quadratic algebraic patches, (b) a bone head, the entire bone was modeled with 5,696 quadratic algebraic patches, and (c) a knot modeled with 6,912 quadratic algebraic patches.
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Quadric Surface Patches
(a) A vase modeled with 336 quadratic algebraic patches, rendered with transparency to show some of its trunctets. (b) The same vase in an environment with multiple light sources and participating media.
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Properties of Quadric Surfaces
• Let QA (QB) denotes the matrix representation of quadric surface in frame A(B), M denotes an affine transformation from frame A to from B
Then the transformation of quadrics is
QB=MTQAM
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Properties of Quadric Surfaces
• Let Qu denotes upper-left 3×3 sub-matrix of Q
The rank of both Q and Qu are invariant under affine transformation
The type of quadric surface is invariant under affine transformations
The quadric surfaces are invariant under rigid motions
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Characteristic Function
• Characteristic functions areDet(Q-λI) Det(Qu-λI)
Invariant under rigid motionUsed for classifying the type of quadrics according to its eignvalues
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Characteristic Function (1)
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Characteristic Function (2)
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Types of Quadric Surfaces • Types are decided by using a decision tree
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Ruled Quadric Surfaces
• Ruled Quadric SurfacesA family of straight lines can be found which lie entirely on the quadric surfacecylinders, cones, hyperbolic paraboloid, hyperboloid of one sheet
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Pencils of two Quadric Surfaces
• F1(x,y,z) and F2(x,y,z) are two quadric surfaces, then the pencil of them is
F1(x,y,z)+αF2(x,y,z)where α is real scalar
Every quadric surface in the pencil of F1(x,y,z) and F2(x,y,z) pass the intersection curves of F1(x,y,z) and F2(x,y,z)
F1(x,y,z)=0 and F2(x,y,z)=0Thus
F1(x,y,z)+αF2(x,y,z)=0
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Pencils of two Quadric Surface
At least one ruled quadric in the pencil of any two general quadrics
Ruled quadrics are easily parameterized The quadric surface intersection curves can be expressed parametrically using the parameterization scheme for the ruled quadric in the pencil
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Representation of Quadric Surfaces
• Two representation techniques:AlgebraicGeometric
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Algebraic Representation of Quadric Surfaces
• Represented by ten coefficients of quadric implicit polynomial equation F(x,y,z):
Advantage: a common set of routines can be written for handling all types of general quadric surfacesDisadvantage: lack of computational robustness
Floating point data of imperfect accuracyInternal inconsistency
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Geometric Representation of Quadric Surfaces
• Represented by {1 point, 2 orthogonal unit vectors, 3 scalars}
The point fixes the position of the surfaceThe vectors define its orientation or axesThe scalars determine its dimensions
• Example: EllipsoidIts center (a point)Two of its three orthogonal axes (two orthogonal unit vectors)Three lengths (radii) along its three axes (three scalars)
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Geometric Representation of Quadric Surfaces
• Advantages: its robustness and internal consistency
• Disadvantage: a large number of routines are needed to handle all the special cases that arise as a result of each type of surface being treated as a separate entity (e.g. a problem of combinatorial explosion in the number of intersection routines)
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Applications of Quadric Surfaces
• A surface/surface or curve/surface intersection: computationally and topologically tractable as compared to parametric patches.
For example, a quadric surface F(x,y,z)=0a line L:(x(t),y(t),z(t)), line and surface intersection F(x(t),y(t),z(t))=0 is a uni-variatequadratic function.
• Quadratic algebraic patches with smooth continuity for modeling complex free-form shapes
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Download Course
http://www.cad.zju.edu.cn/home/jqfeng/GM/GM07.zip