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1/66 Department of Computer Science and Engineering Tamal K. Dey The Ohio State University Delaunay Mesh Generation

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Delaunay Mesh Generation. Tamal K. Dey The Ohio State University. Delaunay Mesh Generation. Automatic mesh generation with good quality. Delaunay refinements: The Delaunay triangulation lends to a proof structure . And it naturally optimizes certain geometric properties. - PowerPoint PPT Presentation

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Page 1: Delaunay Mesh Generation

1/66Department of Computer Science and Engineering

Tamal K. Dey The Ohio State University

Delaunay Mesh Generation

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Delaunay Mesh Generation

• Automatic mesh generation with good quality.

• Delaunay refinements:• The Delaunay triangulation

lends to a proof structure.• And it naturally optimizes

certain geometric properties.

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Basics of Delaunay Refinement

• Pioneered by Chew89, Ruppert92, Shewchuck98

• To mesh some domain D,1. Initialize a set of points S D, compute Del S.2. If some condition is not satisfied, insert a point c

from |D| into S and repeat step 2.3.Return Del S.

• Burden is to show that the algorithm terminates (shown by a packing argument).

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Delsurf =Smooth surface meshing

DelPSC=Delsurf + Protection =PSC meshing

LocPSC=DelPSC+Localization

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Restricted Delaunay

• If the point set is sampled from a domain D.

• We can define the restricted Delaunay triangulation, denoted Del S|D.• Each simplex Del S|D is the

dual of a Voronoi face V that has a nonempty intersection with the domain D.

• Condition to drive Delaunay refinement often uses the restricted Delaunay triangulation as an approximation for D

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Polyhedral Meshing

• Output mesh conforms to input:• All input edges meshed as a

collection of Delaunay edges.• All input facets are meshed with a

collection of Delaunay triangles.• Algorithms with angle

restrictions:• Chew89, Ruppert92, Miller-Talmor-

Teng-Walkington95, Shewchuk98.• Small angles allowed:

• Shewchuk00, Cohen-Steiner-Verdiere-Yvinec02, Cheng-Poon03, Cheng-Dey-Ramos-Ray04, Pav-Walkington04.

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Smooth Surface Meshing

• Input mesh is either an implicit surface or a polygonal mesh approximating a smooth surface

• Output mesh approximates input geometry, conforms to input topology:• No guarantees:

• Chew93.• Skin surfaces:

• Cheng-D.-Edelsbrunner-Sullivan01.• Provable surface algorithms:

• Boissonnat-Oudot03 and Cheng-D.-Ramos-Ray04.

• Interior Volumes:• Oudot-Rineau-Yvinec06.

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Local Feature Size (Smooth) [ABE98]

• Local feature size is calculated using the medial axis of a smooth shape.

• f(x) is the distance from a point to the medial axis

• S is an ε-sample of D if any point x of D has a sample within distance εf(x).

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Homeomorphism and Isotopy

• Homeomorphsim: A function f between two topological spaces:• f is a bijection• f and f-1 are both continuous

• Isotopy: A continuous deformation maintaining homeomorphism

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Sampling Theorem

Theorem (Boissonat-Oudot 2005):

If S M is a discrete sample of a smooth surface M so that each x where a Voronoi edge intersects M lies within ef(x) distance from a sample, then for e<0.09, the restricted Delaunay triangulation Del S|M has the following properties:

(i) It is homeomorphic to M (even isotopic).

(ii) Each triangle has normal aligning within O(e) angle to the surface normals

(iii) Hausdorff distance between M and Del S|M is O(e2) of the local feature size.

Theorem:(Amenta-Bern 98, Cheng-Dey-Edelsbrunner-Sullivan 01)

If S M is a discrete e-sample of a smooth surface M, then for e< 0.09 the restricted Delaunay triangulation Del S|M has the following properties:

Sampling Theorem Modified

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Basic Delaunay Refinement

1. Initialize a set of points S M, compute Del S.

2. If some condition is not satisfied, insert a point c from M into S and repeat step 2.

3. Return Del S|M.

Surface Delaunay Refinement

2. If some Voronoi edge intersects M at x with d(x,S)> ef(x) insert x in S.

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Difficulty

• How to compute f(x)?• Special surfaces such as

skin surfaces allow easy computation of f(x) [CDES01]

• Can be approximated by computing approximate medial axis, needs a dense sample.

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A Solution

• Replace d(x,S)< ef(x) with d(x,S)<l, an user parameter

• But, this does not guarantee any topology

• Require that triangles around vertices form topological disks [Cheng-Dey-Ramos 04]

• Guarantees that output is a manifold

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A Solution

1. Initialize a set of points S M, compute Del S.

2. If some Voronoi edge intersects M at x with d(x,S)>ef(x) insert x in S, and repeat step 2.

2. (b)If restricted triangles around a vertex p do not form a topological disk, insert furthest x where a dual Voronoi edge of a triangle around p intersects M.

3. Return Del S|M.

2. (a) If some Voronoi edge intersects M at x with d(x,S)> l insert x in S, and repeat step 2(a).

Algorithm DelSurf(M,l)

X=center of largest Surface Delaunay ballx

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A MeshingTheorem

Theorem:

The algorithm DelSurf produces output mesh with the following guarantees:

(i) The output mesh is always a 2-manifold

(ii) If l is sufficiently small, the output mesh satisfies topological and geometric guarantees:

1. It is related to M with an isotopy. 2. Each triangle has normal aligning within O(l) angle to the

surface normals3. Hausdorff distance between S and Del S|M is O(l2) of the

local feature size.

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Implicit surface

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Remeshing

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PSCs – A Large Input Class[Cheng-D.-Ramos 07]

• Piecewise smooth complexes (PSCs) include:• Polyhedra• Smooth Surfaces• Piecewise-smooth Surfaces• Non-manifolds

&

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PSCs – A Large Class

• A domain D is a PSC if:• Each k-dimensional element is a manifold

and compact subset of a smooth (C2) k-manifold, 0≤k≤3.

• The k-th stratum, Dk, is the set of k-dim elements of D (k-faces).

• D satisfies usual reqs for being a complex.• Element interiors are disjoint and for σ D,

bd σ D.• For any σ, D, either σ = or σ

D .• D1 is set of elements which are sharp or

non-manifold features (highlighted in red)

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Protecting Ridges

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Delsurf + Protection = DelPSC

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DelPSC Algorithm[Cheng-D.-Ramos-Levine 07,08]

DelPSC(D, λ)1. Protect ridges of D using protection balls. 2. Refine in the weighted Delaunay by turning the balls

into weighted points.

1.Refine a triangle if it has orthoradius > λ2.Refine a triangle or a ball if disk condition is violated3.Refine a ball if it is too big (with respect to λ)

3. Return i Deli S|Di

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Guarantees for DelPSC

1. Manifold• For each σ D2, triangles in Del

S|σ are a manifold with vertices only in σ. Further, their boundary is homeomorphic to bd σ with vertices only in σ.

2. Granularity• There exists some λ > 0 so that

the output of DelPSC(D, λ) is homeomorphic to D.

• This homeomorphism respects stratification, For 0 ≤ i ≤ 2, and σ Di, Del S|σ is homemorphic to σ too.

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Reducing λ

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Examples

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Delsurf + Protection + Localization

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Delaunay Refinement Limitations

•Traditional refinement maintains Delaunay triangulation in memory

•This does not scale well•Causes memory thrashing•May be aborted by OS

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Localization

•A simple algorithm that avoids the scaling issues of the Delaunay triangulation•Avoids memory thrashing•Topological and geometric guarantees•Guarantee of termination•Potentially parallelizable

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A Natural Solution

•Use an octree T to divide S and process points in each node v of T separately

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Two Concerns

• Termination• Mesh consistency

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Termination Trouble

•A locally furthest point in node v can be very close to a point in other nodes

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Messing Mesh Consistency

• Individual meshes do not blend consistently across boundaries

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LocDel Algorithm: Overview

•Process nodes from a queue Q•Refines nodes with parameter λ if there

are violations

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Splitting

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Refining node

•Augment

•Assemble R=NUS

•Compute Del R|M•Refine•Surface Delaunay

ball larger than λ•Fp Del R|M is not a

disk

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Modified Point Insertions

•Modified insertion strategy•If nearest point s

ϵ S to p* is within λ/8 and s ≠ p, then add s to R

•Else add p* to R

•p* augments S, but s does not

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Reprocessing nodes for Consistency

•Needed for mesh consistency•Suppose s is added•Enqueue each node ' ≠ s.t. d(s, ') ≤ 2λ

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Maintaining light structures

• For each node keep:• S = S ∩ •Up ϵ S Fp

• Output: union of surface stars Up ϵ S Fp

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Termination

• insertions are finite, so are enqueues and splits• Augmenting R by an existing point does not

grow S• Consider inserting a new point s

•Nearest point ≠ p → at least λ/8 from S• Insertion due to triangle size → at least λ from S • Else → at least εM from S by our result in Voronoi

point sampling:

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Mesh Theorem for Localization

Theorem:

•output mesh is a 2-manifold without boundary for any l.

•Each point in the output is within distance λ of M

• λ*>0 s.t. if λ<λ* the output is isotopic to M with Hausdorff distance of O(λ2)

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Results

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Results

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Localized Volume Meshing (SGP 2011)

• Extension of LocDel to volume meshing• Leverage existing results for proofs

• Dey-Levine-Slatton 10• Oudot-Rineau-Yvinec 05

• We prove• Termination• Geometric closeness of output to input• For small λ:

• Output is isotopic to input• Hausdorff distance O(λ2)

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LocVol

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LocVol

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Conclusions

Localized versions with certified geometry and topology

Localized versions for PSCs [D.-Slatton13]

Software available fromhttp://www.cse.ohio-state.edu/~tamaldey/surfremesh.html

http://www.cse.ohio-state.edu/~tamaldey/delpsc.html

http://www.cse.ohio-state.edu/~tamaldey/locpsc.html

Acknowledgement: NSF, CGAL

A book Delaunay Mesh Generation: S.-W. Cheng, T. Dey, J. Shewchuk (2012)

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Thank You!