Delaunay Triangulations-Part II - Yazdcs.yazd.ac.ir/farshi/Teaching/CG3931/Slides/Delaunay...

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Review Computing the Delaunay Triangulation Analysis Conclusion Department of Computer Science, Yazd University Delaunay Triangulations-Part II A.Rahiminasab December 2014 1 / 52

Transcript of Delaunay Triangulations-Part II - Yazdcs.yazd.ac.ir/farshi/Teaching/CG3931/Slides/Delaunay...

Page 1: Delaunay Triangulations-Part II - Yazdcs.yazd.ac.ir/farshi/Teaching/CG3931/Slides/Delaunay Triangulations... · Review Computing the Delaunay Triangulation Analysis Conclusion Department

ReviewComputing the Delaunay Triangulation

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Department of Computer Science, Yazd University

Delaunay Triangulations-Part II

A.Rahiminasab

December 20141 / 52

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Triangulations of Planar Point SetsThe Delaunay Triangulation

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Purpose: Approximating a terrain by constructing a polyhedralterrain from a set P of sample points.

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Triangulations of Planar Point SetsThe Delaunay Triangulation

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Theorem 9.1:Let P ={p1, p2, ..., pn} be a point set. A triangulation of P is amaximal planar subdivision with vertex set P .

+ triangles= 2n − 2 − k Back

+ edges= 3n − 3 − k

where k is the number of points in P on the convex hull of P

Theorem 9.2:(Thales Theorem)Let C be a circle,L a line intersecting C in points a and b, andp,q,r and s points lying on the same side of L.Suppose that pand q lie on C, that r lies inside C,and that s lies outside C.Then

∠arb > ∠abq = ∠aqb > ∠asb

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Observation 9.3:Let T be a triangulation with an illegal edge e.Let T ′ be thetriangulation obtained from T by flipping e.Then

A(T ′) > A(T )

Definition:A legal triangulation is a triangulation that does not contain anyillegal edge.

Conclusion:Any angle-optimal triangulation is legal.

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Triangulations of Planar Point SetsThe Delaunay Triangulation

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Observation 9.3:Let T be a triangulation with an illegal edge e.Let T ′ be thetriangulation obtained from T by flipping e.Then

A(T ′) > A(T )

Definition:A legal triangulation is a triangulation that does not contain anyillegal edge.

Conclusion:Any angle-optimal triangulation is legal.

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Triangulations of Planar Point SetsThe Delaunay Triangulation

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Observation 9.3:Let T be a triangulation with an illegal edge e.Let T ′ be thetriangulation obtained from T by flipping e.Then

A(T ′) > A(T )

Definition:A legal triangulation is a triangulation that does not contain anyillegal edge.

Conclusion:Any angle-optimal triangulation is legal.

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Lemma 9.4:Let edge pipj be incident to triangles pipjpk and pipjpl and letC be the circle through pi,pj and pk. The edge pipj is illegal ifand only if the point pl lies in the interior of C.

+ if the points pi,pj ,pk,pl from a convex quadrilateral and donot lie on a common circle ⇒ exactly one of pipj and pkplis an illegal edge. Back

Pk

Pi

PjPl

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Triangulations of Planar Point SetsThe Delaunay Triangulation

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Lemma 9.4:Let edge pipj be incident to triangles pipjpk and pipjpl and letC be the circle through pi,pj and pk. The edge pipj is illegal ifand only if the point pl lies in the interior of C.

+ if the points pi,pj ,pk,pl from a convex quadrilateral and donot lie on a common circle ⇒ exactly one of pipj and pkplis an illegal edge. Back

Pk

Pi

PjPl

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Triangulations of Planar Point SetsThe Delaunay Triangulation

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Lemma 9.4:Let edge pipj be incident to triangles pipjpk and pipjpl and letC be the circle through pi,pj and pk. The edge pipj is illegal ifand only if the point pl lies in the interior of C.

+ if the points pi,pj ,pk,pl from a convex quadrilateral and donot lie on a common circle ⇒ exactly one of pipj and pkplis an illegal edge. Back

Pk

Pi

PjPl

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1 A set P of n points in the plane2 The Voronoi diagram V or(P ) is

the subdivision of the plane intoVoronoi cells V (p) for all p ∈P

3 Let G be the dual graph ofV or(P )

4 The Delaunay graph DG(P ) isthe straight line embedding of G.

Back

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Triangulations of Planar Point SetsThe Delaunay Triangulation

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1 A set P of n points in the plane2 The Voronoi diagram V or(P ) is

the subdivision of the plane intoVoronoi cells V (p) for all p ∈P

3 Let G be the dual graph ofV or(P )

4 The Delaunay graph DG(P ) isthe straight line embedding of G.

Back

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Triangulations of Planar Point SetsThe Delaunay Triangulation

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1 A set P of n points in the plane2 The Voronoi diagram V or(P ) is

the subdivision of the plane intoVoronoi cells V (p) for all p ∈P

3 Let G be the dual graph ofV or(P )

4 The Delaunay graph DG(P ) isthe straight line embedding of G.

Back

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Triangulations of Planar Point SetsThe Delaunay Triangulation

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1 A set P of n points in the plane2 The Voronoi diagram V or(P ) is

the subdivision of the plane intoVoronoi cells V (p) for all p ∈P

3 Let G be the dual graph ofV or(P )

4 The Delaunay graph DG(P ) isthe straight line embedding of G.

Back

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Triangulations of Planar Point SetsThe Delaunay Triangulation

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Lemma 9.5:The Delaunay graph of a planar point set is a plane graph.

The edge pipj is in the Delaunay graph Dg(P )⇐⇒there is aCij whit pi and pj on its boundary and no other site of Pcontained in it.The center of such a disc lies on the common edge of V (pi)and V (pj).

+ If the point set P is in general position then the Delaunaygraph is a triangulation.

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Theorem 9.6:Back Let P be a set of points in the plane,

Three points pi,pj ,pk ∈P are vertices of the same face ofthe Delaunay graph of P ⇐⇒ the circle through pi,pj ,pkcontains no point of P in its interior.Two points pi,pj ∈P form an edge of the Delaunay graph ofP ⇐⇒ there is a closed disc C that contains pi and pj onits boundary and does not contain any other point of P .

Theorem 9.7:T is a Delaunay triangulation of P ⇐⇒ the circumcircle of anytriangle of T does not contain a point of P in its interior.

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Triangulations of Planar Point SetsThe Delaunay Triangulation

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Theorem 9.8:Let P be a set of points in the plane.A triangulation T of P islegal ⇐⇒ T is a Delaunay triangulation P .

Theorem 9.9:Let P be a set of points in the plane.Any angle-optimaltriangulation of P is a Delaunay triangulation P .Furthermore,any Delaunay triangulation of P maximizes theminimum angle over all triangulations ofP .

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Triangulations of Planar Point SetsThe Delaunay Triangulation

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A Delaunay triangulation for a set P of points in a plane is atriangulation DT (P ) such that no point in P is inside thecircumcircle of any triangle in DT (P ).

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Delaunay triangulations maximize the minimum angle of allthe angles of the triangles in the triangulation; they tend toavoid skinny triangles.For a set of points on the same line there is no Delaunaytriangulation (the notion of triangulation is degenerate forthis case)For four or more points on the same circle (e.g., thevertices of a rectangle) the Delaunay triangulation is notuniqueBy considering circumscribed spheres, the notion ofDelaunay triangulation extends to three and higherdimensions

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Triangulations of Planar Point SetsThe Delaunay Triangulation

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Delaunay triangulations maximize the minimum angle of allthe angles of the triangles in the triangulation; they tend toavoid skinny triangles.For a set of points on the same line there is no Delaunaytriangulation (the notion of triangulation is degenerate forthis case)For four or more points on the same circle (e.g., thevertices of a rectangle) the Delaunay triangulation is notuniqueBy considering circumscribed spheres, the notion ofDelaunay triangulation extends to three and higherdimensions

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Triangulations of Planar Point SetsThe Delaunay Triangulation

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Delaunay triangulations maximize the minimum angle of allthe angles of the triangles in the triangulation; they tend toavoid skinny triangles.For a set of points on the same line there is no Delaunaytriangulation (the notion of triangulation is degenerate forthis case)For four or more points on the same circle (e.g., thevertices of a rectangle) the Delaunay triangulation is notuniqueBy considering circumscribed spheres, the notion ofDelaunay triangulation extends to three and higherdimensions

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Triangulations of Planar Point SetsThe Delaunay Triangulation

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Delaunay triangulations maximize the minimum angle of allthe angles of the triangles in the triangulation; they tend toavoid skinny triangles.For a set of points on the same line there is no Delaunaytriangulation (the notion of triangulation is degenerate forthis case)For four or more points on the same circle (e.g., thevertices of a rectangle) the Delaunay triangulation is notuniqueBy considering circumscribed spheres, the notion ofDelaunay triangulation extends to three and higherdimensions

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Triangulations of Planar Point SetsThe Delaunay Triangulation

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The triangulation is named after Boris Delaunay for hiswork on this topic from 1934.

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Triangulations of Planar Point SetsThe Delaunay Triangulation

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The voronoi diagram is named after Georgy F. Voronoi forhis work on this topic.

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Delaunay triangulations help in constructing various things:Euclidean Minimum Spanning TreesApproximations to the Euclidean Traveling SalespersonProblem, ...

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There are several ways to compute the Delaunay triangulation:By plane sweepBy iterative flipping from any triangulationBy conversion from the Voronoi diagram Go to diagram

By randomized incremental approach√

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UsageMethodsDescription of the fourth methodAlgorithmPoint location structure

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There are several ways to compute the Delaunay triangulation:By plane sweepBy iterative flipping from any triangulationBy conversion from the Voronoi diagram Go to diagram

By randomized incremental approach√

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AnalysisConclusion

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AnalysisConclusion

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Randomized incremental approach

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AnalysisConclusion

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Randomized incremental approach

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AnalysisConclusion

UsageMethodsDescription of the fourth methodAlgorithmPoint location structure

Randomized incremental approach

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AnalysisConclusion

UsageMethodsDescription of the fourth methodAlgorithmPoint location structure

Randomized incremental approach

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AnalysisConclusion

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AnalysisConclusion

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Randomized incremental approach

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AnalysisConclusion

UsageMethodsDescription of the fourth methodAlgorithmPoint location structure

Randomized incremental approach

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ReviewComputing the Delaunay Triangulation

AnalysisConclusion

UsageMethodsDescription of the fourth methodAlgorithmPoint location structure

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ReviewComputing the Delaunay Triangulation

AnalysisConclusion

UsageMethodsDescription of the fourth methodAlgorithmPoint location structure

Randomized incremental approach

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ReviewComputing the Delaunay Triangulation

AnalysisConclusion

UsageMethodsDescription of the fourth methodAlgorithmPoint location structure

Randomized incremental approach

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ReviewComputing the Delaunay Triangulation

AnalysisConclusion

UsageMethodsDescription of the fourth methodAlgorithmPoint location structure

Randomized incremental approach

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ReviewComputing the Delaunay Triangulation

AnalysisConclusion

UsageMethodsDescription of the fourth methodAlgorithmPoint location structure

Randomized incremental approach

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AnalysisConclusion

UsageMethodsDescription of the fourth methodAlgorithmPoint location structure

Randomized incremental approach

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AnalysisConclusion

UsageMethodsDescription of the fourth methodAlgorithmPoint location structure

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ReviewComputing the Delaunay Triangulation

AnalysisConclusion

UsageMethodsDescription of the fourth methodAlgorithmPoint location structure

Randomized incremental approach

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ReviewComputing the Delaunay Triangulation

AnalysisConclusion

UsageMethodsDescription of the fourth methodAlgorithmPoint location structure

Randomized incremental approach

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AnalysisConclusion

UsageMethodsDescription of the fourth methodAlgorithmPoint location structure

Randomized incremental approach

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ReviewComputing the Delaunay Triangulation

AnalysisConclusion

UsageMethodsDescription of the fourth methodAlgorithmPoint location structure

Randomized incremental approach

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ReviewComputing the Delaunay Triangulation

AnalysisConclusion

UsageMethodsDescription of the fourth methodAlgorithmPoint location structure

Randomized incremental approach

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ReviewComputing the Delaunay Triangulation

AnalysisConclusion

UsageMethodsDescription of the fourth methodAlgorithmPoint location structure

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ReviewComputing the Delaunay Triangulation

AnalysisConclusion

UsageMethodsDescription of the fourth methodAlgorithmPoint location structure

Randomized incremental approach

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UsageMethodsDescription of the fourth methodAlgorithmPoint location structure

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UsageMethodsDescription of the fourth methodAlgorithmPoint location structure

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UsageMethodsDescription of the fourth methodAlgorithmPoint location structure

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UsageMethodsDescription of the fourth methodAlgorithmPoint location structure

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AnalysisConclusion

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PseudocodeBack

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AnalysisConclusion

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Randomized incremental approach

Lemma 9.4

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AnalysisConclusion

UsageMethodsDescription of the fourth methodAlgorithmPoint location structure

Randomized incremental approach

Butwhat about the correctness of algorithm?

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ReviewComputing the Delaunay Triangulation

AnalysisConclusion

UsageMethodsDescription of the fourth methodAlgorithmPoint location structure

Randomized incremental approach

Must show no illegal edge left behind!

We see that every new edge added is incident to Pr .We will see that every new edge added is in fact legal.Together with the fact that an edge can only become illegalif one of its incident triangles changes,then our algorithmtests any edge that may become illegal.

The algorithm is correct

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ReviewComputing the Delaunay Triangulation

AnalysisConclusion

UsageMethodsDescription of the fourth methodAlgorithmPoint location structure

Randomized incremental approach

Must show no illegal edge left behind!

We see that every new edge added is incident to Pr .We will see that every new edge added is in fact legal.Together with the fact that an edge can only become illegalif one of its incident triangles changes,then our algorithmtests any edge that may become illegal.

The algorithm is correct

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ReviewComputing the Delaunay Triangulation

AnalysisConclusion

UsageMethodsDescription of the fourth methodAlgorithmPoint location structure

Randomized incremental approach

Must show no illegal edge left behind!

We see that every new edge added is incident to Pr .We will see that every new edge added is in fact legal.Together with the fact that an edge can only become illegalif one of its incident triangles changes,then our algorithmtests any edge that may become illegal.

The algorithm is correct

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ReviewComputing the Delaunay Triangulation

AnalysisConclusion

UsageMethodsDescription of the fourth methodAlgorithmPoint location structure

Randomized incremental approach

Must show no illegal edge left behind!

We see that every new edge added is incident to Pr .We will see that every new edge added is in fact legal.Together with the fact that an edge can only become illegalif one of its incident triangles changes,then our algorithmtests any edge that may become illegal.

The algorithm is correct

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ReviewComputing the Delaunay Triangulation

AnalysisConclusion

UsageMethodsDescription of the fourth methodAlgorithmPoint location structure

Randomized incremental approach

Must show no illegal edge left behind!

We see that every new edge added is incident to Pr .We will see that every new edge added is in fact legal.Together with the fact that an edge can only become illegalif one of its incident triangles changes,then our algorithmtests any edge that may become illegal.

The algorithm is correct

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ReviewComputing the Delaunay Triangulation

AnalysisConclusion

UsageMethodsDescription of the fourth methodAlgorithmPoint location structure

Randomized incremental approach

Lemma 9.10:Every new edge created in ’DELAUNAYTRIANGULATION’ or in’LEGALIZEEDGE’ during the insertion of Pr is an edge of theDelaunay graph of {p−1, p−2, p0, ..., pr}

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ReviewComputing the Delaunay Triangulation

AnalysisConclusion

UsageMethodsDescription of the fourth methodAlgorithmPoint location structure

Randomized incremental approach

Lemma 9.10:Every new edge created in ’DELAUNAYTRIANGULATION’ or in’LEGALIZEEDGE’ during the insertion of Pr is an edge of theDelaunay graph of {p−1, p−2, p0, ..., pr}

pl

pj pi

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ReviewComputing the Delaunay Triangulation

AnalysisConclusion

UsageMethodsDescription of the fourth methodAlgorithmPoint location structure

Randomized incremental approach

Lemma 9.10:Every new edge created in ’DELAUNAYTRIANGULATION’ or in’LEGALIZEEDGE’ during the insertion of Pr is an edge of theDelaunay graph of {p−1, p−2, p0, ..., pr}

pl

pj pi

pr

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ReviewComputing the Delaunay Triangulation

AnalysisConclusion

UsageMethodsDescription of the fourth methodAlgorithmPoint location structure

Randomized incremental approach

Lemma 9.10:Every new edge created in ’DELAUNAYTRIANGULATION’ or in’LEGALIZEEDGE’ during the insertion of Pr is an edge of theDelaunay graph of {p−1, p−2, p0, ..., pr}

pl

pj pi

pr

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ReviewComputing the Delaunay Triangulation

AnalysisConclusion

UsageMethodsDescription of the fourth methodAlgorithmPoint location structure

Randomized incremental approach

Lemma 9.10:Every new edge created in ’DELAUNAYTRIANGULATION’ or in’LEGALIZEEDGE’ during the insertion of Pr is an edge of theDelaunay graph of {p−1, p−2, p0, ..., pr}

pl

pj pi

pr

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ReviewComputing the Delaunay Triangulation

AnalysisConclusion

UsageMethodsDescription of the fourth methodAlgorithmPoint location structure

Randomized incremental approach

Lemma 9.10:Every new edge created in ’DELAUNAYTRIANGULATION’ or in’LEGALIZEEDGE’ during the insertion of Pr is an edge of theDelaunay graph of {p−1, p−2, p0, ..., pr}

pl

pj pi

pr

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ReviewComputing the Delaunay Triangulation

AnalysisConclusion

UsageMethodsDescription of the fourth methodAlgorithmPoint location structure

Randomized incremental approach

Lemma 9.10:Every new edge created in ’DELAUNAYTRIANGULATION’ or in’LEGALIZEEDGE’ during the insertion of Pr is an edge of theDelaunay graph of {p−1, p−2, p0, ..., pr}

pl

pj pi

pr

C

C’

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AnalysisConclusion

UsageMethodsDescription of the fourth methodAlgorithmPoint location structure

How to find the triangle containing the point pr ?Go to algorithm

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ReviewComputing the Delaunay Triangulation

AnalysisConclusion

UsageMethodsDescription of the fourth methodAlgorithmPoint location structure

introduction DAG

- A point location structure D is a directed acyclic graph.

The leaves of D correspond to the triangles of the currenttriangulation T✓ exist cross-pointers between those leaves and thetriangulation.The internal nodes of D correspond to triangles that havealready been destroyed✓ Any internal node gets at most three outgoing pointers.

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ReviewComputing the Delaunay Triangulation

AnalysisConclusion

UsageMethodsDescription of the fourth methodAlgorithmPoint location structure

introduction DAG

- A point location structure D is a directed acyclic graph.

The leaves of D correspond to the triangles of the currenttriangulation T✓ exist cross-pointers between those leaves and thetriangulation.The internal nodes of D correspond to triangles that havealready been destroyed✓ Any internal node gets at most three outgoing pointers.

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AnalysisConclusion

UsageMethodsDescription of the fourth methodAlgorithmPoint location structure

Constructing DAG

P 0

P -1

P -2

41

41

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AnalysisConclusion

UsageMethodsDescription of the fourth methodAlgorithmPoint location structure

Constructing DAG

P 0

P -1

P -2

42

43 44

41

42 4344

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AnalysisConclusion

UsageMethodsDescription of the fourth methodAlgorithmPoint location structure

Constructing DAG

P 0

P -1

P -2

45

46 4741

42 4344

45 4647

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AnalysisConclusion

UsageMethodsDescription of the fourth methodAlgorithmPoint location structure

Constructing DAG

P 0

P -1

P -2

48

49 411

410

41

42 4344

45 4647 48 49 410

411

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AnalysisConclusion

UsageMethodsDescription of the fourth methodAlgorithmPoint location structure

Constructing DAG

P 0

P -1

P -2

412

413 414

41

42 4344

45 4647 48 49 410

411

412 413414

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AnalysisConclusion

UsageMethodsDescription of the fourth methodAlgorithmPoint location structure

Constructing DAG

P 0

P -1

P -2

41

42 4344

45 4647 48 49 410

411

412 413414

415 416

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ReviewComputing the Delaunay Triangulation

AnalysisConclusion

UsageMethodsDescription of the fourth methodAlgorithmPoint location structure

Constructing DAG

P 0

P -1

P -2

415

416

41

42 4344

45 4647 48 49 410

411

412 413414

415 416

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ReviewComputing the Delaunay Triangulation

AnalysisConclusion

UsageMethodsDescription of the fourth methodAlgorithmPoint location structure

Point location

1 Start at the root of D,2 Check the three children of the root and descend to the

corresponding child,3 check the children of this node,descend to a child whose

triangle contains pr,...

4 until we reach a leaf of D,this leaf corresponding to atriangle in the current triangulation that contains pr.

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AnalysisConclusion

UsageMethodsDescription of the fourth methodAlgorithmPoint location structure

How to choose p−1 and p−2?

and

How to implement the test of whether an edge is legal?

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AnalysisConclusion

UsageMethodsDescription of the fourth methodAlgorithmPoint location structure

The first issue

P 0

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AnalysisConclusion

UsageMethodsDescription of the fourth methodAlgorithmPoint location structure

The first issue

L−1p−1

P 0

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AnalysisConclusion

UsageMethodsDescription of the fourth methodAlgorithmPoint location structure

The first issue

L−1

L−2

p−1

P 0

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AnalysisConclusion

UsageMethodsDescription of the fourth methodAlgorithmPoint location structure

The first issue

L−1

L−2

p−1

p−2

P 0

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AnalysisConclusion

UsageMethodsDescription of the fourth methodAlgorithmPoint location structure

The first issue

L−1

L−2

p−1

p−2

P 0

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AnalysisConclusion

UsageMethodsDescription of the fourth methodAlgorithmPoint location structure

The first issue

Position of a point pj with respect to the oriented line from pi topk:

pj lies to the left of the line from pi to p−1;pj lies to the left of the line from p−2 to pi;pj is lexicographically larger than pi.By our choice of p−1 and p−2, the above conditions areequivalent.

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AnalysisConclusion

UsageMethodsDescription of the fourth methodAlgorithmPoint location structure

The second issue

Let pipj be the edge of to be tested,and let pk and pl be theother vertices of the triangles incident to pipj (if they exist).

pipj is an edge of the triangle p0p−1p−2. These edges arealways legal.The indices i,j,k,l are all non-negative.←Ð this case isnormalAll other cases pipj is legal if and only if min(k,l) < min(i,j)

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ReviewComputing the Delaunay Triangulation

AnalysisConclusion

The Analysis

Lemma 9.11:The expected number of triangles created by the algorithm is atmost 9n + 1.

Proof.Pr := {p1, p2, ..., pr} Dgr := Dg({p−2, p−1, p0}∪Pr)

♯(new triangles in step r)≤ 2k - 3 k=deg(pr,Dgr)

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ReviewComputing the Delaunay Triangulation

AnalysisConclusion

The Analysis

Lemma 9.11:The expected number of triangles created by the algorithm is atmost 9n + 1.

Proof.Pr := {p1, p2, ..., pr} Dgr := Dg({p−2, p−1, p0}∪Pr)

♯(new triangles in step r)≤ 2k - 3 k=deg(pr,Dgr)

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ReviewComputing the Delaunay Triangulation

AnalysisConclusion

The Analysis

degree of pr, over all possible permutations of the set P?+ Backwards analysis:

By Theorem 7.3: ♯ Edges in Dgr ≤ 3(r + 3) - 6Total degree of the vertices in Pr < 2[3(r + 3) - 9] = 6rThe expected degree of a random point of Pr ≤ 6we can bound the number of triangles created in step r:

E[♯ (△s in step r)]≤ E [2deg(pr,Dgr) - 3]

= 2E[deg(pr,Dgr)] - 3≤ 2 × 6 - 3 = 9

Total number of △s is at most 9n + 141 / 52

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ReviewComputing the Delaunay Triangulation

AnalysisConclusion

The Analysis

degree of pr, over all possible permutations of the set P?+ Backwards analysis:

By Theorem 7.3: ♯ Edges in Dgr ≤ 3(r + 3) - 6Total degree of the vertices in Pr < 2[3(r + 3) - 9] = 6rThe expected degree of a random point of Pr ≤ 6we can bound the number of triangles created in step r:

E[♯ (△s in step r)]≤ E [2deg(pr,Dgr) - 3]

= 2E[deg(pr,Dgr)] - 3≤ 2 × 6 - 3 = 9

Total number of △s is at most 9n + 141 / 52

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ReviewComputing the Delaunay Triangulation

AnalysisConclusion

The Analysis

degree of pr, over all possible permutations of the set P?+ Backwards analysis:

By Theorem 7.3: ♯ Edges in Dgr ≤ 3(r + 3) - 6Total degree of the vertices in Pr < 2[3(r + 3) - 9] = 6rThe expected degree of a random point of Pr ≤ 6we can bound the number of triangles created in step r:

E[♯ (△s in step r)]≤ E [2deg(pr,Dgr) - 3]

= 2E[deg(pr,Dgr)] - 3≤ 2 × 6 - 3 = 9

Total number of △s is at most 9n + 141 / 52

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ReviewComputing the Delaunay Triangulation

AnalysisConclusion

The Analysis

degree of pr, over all possible permutations of the set P?+ Backwards analysis:

By Theorem 7.3: ♯ Edges in Dgr ≤ 3(r + 3) - 6Total degree of the vertices in Pr < 2[3(r + 3) - 9] = 6rThe expected degree of a random point of Pr ≤ 6we can bound the number of triangles created in step r:

E[♯ (△s in step r)]≤ E [2deg(pr,Dgr) - 3]

= 2E[deg(pr,Dgr)] - 3≤ 2 × 6 - 3 = 9

Total number of △s is at most 9n + 141 / 52

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ReviewComputing the Delaunay Triangulation

AnalysisConclusion

The Analysis

degree of pr, over all possible permutations of the set P?+ Backwards analysis:

By Theorem 7.3: ♯ Edges in Dgr ≤ 3(r + 3) - 6Total degree of the vertices in Pr < 2[3(r + 3) - 9] = 6rThe expected degree of a random point of Pr ≤ 6we can bound the number of triangles created in step r:

E[♯ (△s in step r)]≤ E [2deg(pr,Dgr) - 3]

= 2E[deg(pr,Dgr)] - 3≤ 2 × 6 - 3 = 9

Total number of △s is at most 9n + 141 / 52

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ReviewComputing the Delaunay Triangulation

AnalysisConclusion

The Analysis

Lemma 9.12:The Delaunay triangulation can be computed in O(nlogn)expected time, using O(n) expected storage.

Proof.

Space follows from nodes in D representing trianglescreated, which by the previous lemma is O(n).Not counting the time for point location,the creation of each triangle takes O(1) time,so the total time will be O(n) + time for point locations (onexpectation).

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ReviewComputing the Delaunay Triangulation

AnalysisConclusion

The Analysis

Lemma 9.12:The Delaunay triangulation can be computed in O(nlogn)expected time, using O(n) expected storage.

Proof.

Space follows from nodes in D representing trianglescreated, which by the previous lemma is O(n).Not counting the time for point location,the creation of each triangle takes O(1) time,so the total time will be O(n) + time for point locations (onexpectation).

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ReviewComputing the Delaunay Triangulation

AnalysisConclusion

The Analysis

Lemma 9.12:The Delaunay triangulation can be computed in O(nlogn)expected time, using O(n) expected storage.

Proof.

Space follows from nodes in D representing trianglescreated, which by the previous lemma is O(n).Not counting the time for point location,the creation of each triangle takes O(1) time,so the total time will be O(n) + time for point locations (onexpectation).

42 / 52

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ReviewComputing the Delaunay Triangulation

AnalysisConclusion

The Analysis

Lemma 9.12:The Delaunay triangulation can be computed in O(nlogn)expected time, using O(n) expected storage.

Proof.

Space follows from nodes in D representing trianglescreated, which by the previous lemma is O(n).Not counting the time for point location,the creation of each triangle takes O(1) time,so the total time will be O(n) + time for point locations (onexpectation).

42 / 52

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ReviewComputing the Delaunay Triangulation

AnalysisConclusion

The Analysis

Let K(△) ⊂ P be the points inside the circumcircle of agiven triangle △Therefore the total time for the point location steps is:

O(n + ∑△

card(K(△)))

∑△

card(K(△))=O(nlogn)?

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ReviewComputing the Delaunay Triangulation

AnalysisConclusion

The Analysis

Let K(△) ⊂ P be the points inside the circumcircle of agiven triangle △Therefore the total time for the point location steps is:

O(n + ∑△

card(K(△)))

∑△

card(K(△))=O(nlogn)?

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ReviewComputing the Delaunay Triangulation

AnalysisConclusion

The Analysis

Let K(△) ⊂ P be the points inside the circumcircle of agiven triangle △Therefore the total time for the point location steps is:

O(n + ∑△

card(K(△)))

∑△

card(K(△))=O(nlogn)?

43 / 52

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ReviewComputing the Delaunay Triangulation

AnalysisConclusion

The Analysis

Lemma 9.13:If P is a point set in general position,then

∑△

card(K(△))= O(nlogn)

Proof.

P is in general position,then every subset Pr is in generalpositiontriangulation after insert pr is the unique triangulation Dgr

Tr:= the set of △s of Dgr

Tr/ Tr−1 = the set of Delaunay △s created in stage r.(by difinition)

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ReviewComputing the Delaunay Triangulation

AnalysisConclusion

The Analysis

Lemma 9.13:If P is a point set in general position,then

∑△

card(K(△))= O(nlogn)

Proof.

P is in general position,then every subset Pr is in generalpositiontriangulation after insert pr is the unique triangulation Dgr

Tr:= the set of △s of Dgr

Tr/ Tr−1 = the set of Delaunay △s created in stage r.(by difinition)

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ReviewComputing the Delaunay Triangulation

AnalysisConclusion

The Analysis

Lemma 9.13:If P is a point set in general position,then

∑△

card(K(△))= O(nlogn)

Proof.

P is in general position,then every subset Pr is in generalpositiontriangulation after insert pr is the unique triangulation Dgr

Tr:= the set of △s of Dgr

Tr/ Tr−1 = the set of Delaunay △s created in stage r.(by difinition)

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ReviewComputing the Delaunay Triangulation

AnalysisConclusion

The Analysis

Lemma 9.13:If P is a point set in general position,then

∑△

card(K(△))= O(nlogn)

Proof.

P is in general position,then every subset Pr is in generalpositiontriangulation after insert pr is the unique triangulation Dgr

Tr:= the set of △s of Dgr

Tr/ Tr−1 = the set of Delaunay △s created in stage r.(by difinition)

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ReviewComputing the Delaunay Triangulation

AnalysisConclusion

The Analysis

Rewrite the sum:n

∑r=1( ∑△∈Tr∖Tr−1

card(K(△)))

Let k(Pr, q) = ♯ of triangles △ ∈ Tr ; q ∈ K(△)Let k(Pr, q, pr) = ♯ of triangles △ ∈ Tr ; q ∈ K(△) , pr isincident to △so we have:

∑△∈Tr∖Tr−1

card(K(△))= ∑q∈P∖Pr

k(Pr,q,pr)

But E [k(Pr,q,pr)] ≤ ?

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ReviewComputing the Delaunay Triangulation

AnalysisConclusion

The Analysis

Rewrite the sum:n

∑r=1( ∑△∈Tr∖Tr−1

card(K(△)))

Let k(Pr, q) = ♯ of triangles △ ∈ Tr ; q ∈ K(△)Let k(Pr, q, pr) = ♯ of triangles △ ∈ Tr ; q ∈ K(△) , pr isincident to △so we have:

∑△∈Tr∖Tr−1

card(K(△))= ∑q∈P∖Pr

k(Pr,q,pr)

But E [k(Pr,q,pr)] ≤ ?

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ReviewComputing the Delaunay Triangulation

AnalysisConclusion

The Analysis

Rewrite the sum:n

∑r=1( ∑△∈Tr∖Tr−1

card(K(△)))

Let k(Pr, q) = ♯ of triangles △ ∈ Tr ; q ∈ K(△)Let k(Pr, q, pr) = ♯ of triangles △ ∈ Tr ; q ∈ K(△) , pr isincident to △so we have:

∑△∈Tr∖Tr−1

card(K(△))= ∑q∈P∖Pr

k(Pr,q,pr)

But E [k(Pr,q,pr)] ≤ ?

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ReviewComputing the Delaunay Triangulation

AnalysisConclusion

The Analysis

Rewrite the sum:n

∑r=1( ∑△∈Tr∖Tr−1

card(K(△)))

Let k(Pr, q) = ♯ of triangles △ ∈ Tr ; q ∈ K(△)Let k(Pr, q, pr) = ♯ of triangles △ ∈ Tr ; q ∈ K(△) , pr isincident to △so we have:

∑△∈Tr∖Tr−1

card(K(△))= ∑q∈P∖Pr

k(Pr,q,pr)

But E [k(Pr,q,pr)] ≤ ?

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ReviewComputing the Delaunay Triangulation

AnalysisConclusion

The Analysis

Rewrite the sum:n

∑r=1( ∑△∈Tr∖Tr−1

card(K(△)))

Let k(Pr, q) = ♯ of triangles △ ∈ Tr ; q ∈ K(△)Let k(Pr, q, pr) = ♯ of triangles △ ∈ Tr ; q ∈ K(△) , pr isincident to △so we have:

∑△∈Tr∖Tr−1

card(K(△))= ∑q∈P∖Pr

k(Pr,q,pr)

But E [k(Pr,q,pr)] ≤ ?

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ReviewComputing the Delaunay Triangulation

AnalysisConclusion

The Analysis

fix Pr, so k(Pr,q,pr) depends only on pr

Probability that pr is incident to a triangle is 3/rThus:

E [k(Pr,q,pr)] ≤ 3k(Pr,q)r

Using:

∑△∈Tr∖Tr−1

card(K(△))= ∑q∈P∖Pr

k(Pr,q,pr)

We can rewrite our sum as:E[ ∑

△∈Tr∖Tr−1

card(K(△))] ≤ 3r ∑

q∈P∖Pr

k(Pr,q)

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ReviewComputing the Delaunay Triangulation

AnalysisConclusion

The Analysis

fix Pr, so k(Pr,q,pr) depends only on pr

Probability that pr is incident to a triangle is 3/rThus:

E [k(Pr,q,pr)] ≤ 3k(Pr,q)r

Using:

∑△∈Tr∖Tr−1

card(K(△))= ∑q∈P∖Pr

k(Pr,q,pr)

We can rewrite our sum as:E[ ∑

△∈Tr∖Tr−1

card(K(△))] ≤ 3r ∑

q∈P∖Pr

k(Pr,q)

46 / 52

Page 159: Delaunay Triangulations-Part II - Yazdcs.yazd.ac.ir/farshi/Teaching/CG3931/Slides/Delaunay Triangulations... · Review Computing the Delaunay Triangulation Analysis Conclusion Department

ReviewComputing the Delaunay Triangulation

AnalysisConclusion

The Analysis

fix Pr, so k(Pr,q,pr) depends only on pr

Probability that pr is incident to a triangle is 3/rThus:

E [k(Pr,q,pr)] ≤ 3k(Pr,q)r

Using:

∑△∈Tr∖Tr−1

card(K(△))= ∑q∈P∖Pr

k(Pr,q,pr)

We can rewrite our sum as:E[ ∑

△∈Tr∖Tr−1

card(K(△))] ≤ 3r ∑

q∈P∖Pr

k(Pr,q)

46 / 52

Page 160: Delaunay Triangulations-Part II - Yazdcs.yazd.ac.ir/farshi/Teaching/CG3931/Slides/Delaunay Triangulations... · Review Computing the Delaunay Triangulation Analysis Conclusion Department

ReviewComputing the Delaunay Triangulation

AnalysisConclusion

The Analysis

fix Pr, so k(Pr,q,pr) depends only on pr

Probability that pr is incident to a triangle is 3/rThus:

E [k(Pr,q,pr)] ≤ 3k(Pr,q)r

Using:

∑△∈Tr∖Tr−1

card(K(△))= ∑q∈P∖Pr

k(Pr,q,pr)

We can rewrite our sum as:E[ ∑

△∈Tr∖Tr−1

card(K(△))] ≤ 3r ∑

q∈P∖Pr

k(Pr,q)

46 / 52

Page 161: Delaunay Triangulations-Part II - Yazdcs.yazd.ac.ir/farshi/Teaching/CG3931/Slides/Delaunay Triangulations... · Review Computing the Delaunay Triangulation Analysis Conclusion Department

ReviewComputing the Delaunay Triangulation

AnalysisConclusion

The Analysis

fix Pr, so k(Pr,q,pr) depends only on pr

Probability that pr is incident to a triangle is 3/rThus:

E [k(Pr,q,pr)] ≤ 3k(Pr,q)r

Using:

∑△∈Tr∖Tr−1

card(K(△))= ∑q∈P∖Pr

k(Pr,q,pr)

We can rewrite our sum as:E[ ∑

△∈Tr∖Tr−1

card(K(△))] ≤ 3r ∑

q∈P∖Pr

k(Pr,q)

46 / 52

Page 162: Delaunay Triangulations-Part II - Yazdcs.yazd.ac.ir/farshi/Teaching/CG3931/Slides/Delaunay Triangulations... · Review Computing the Delaunay Triangulation Analysis Conclusion Department

ReviewComputing the Delaunay Triangulation

AnalysisConclusion

The Analysis

Any of the remaining n-r points is equally likely to appearas pr+1So:

E[ k(Pr,pr+1)] = 1n−r ∑

q∈P∖Pr

k(Pr,q)

By substitute this into:E[ ∑

△∈Tr∖Tr−1

card(K(△))] ≤ 3r ∑

q∈P∖Pr

k(Pr,q)

We have:E[ ∑

△∈Tr∖Tr−1

card(K(△))] ≤ 3(n−1r )E[k(Pr,pr+1)].

But what is k(Pr,pr+1)?

47 / 52

Page 163: Delaunay Triangulations-Part II - Yazdcs.yazd.ac.ir/farshi/Teaching/CG3931/Slides/Delaunay Triangulations... · Review Computing the Delaunay Triangulation Analysis Conclusion Department

ReviewComputing the Delaunay Triangulation

AnalysisConclusion

The Analysis

Any of the remaining n-r points is equally likely to appearas pr+1So:

E[ k(Pr,pr+1)] = 1n−r ∑

q∈P∖Pr

k(Pr,q)

By substitute this into:E[ ∑

△∈Tr∖Tr−1

card(K(△))] ≤ 3r ∑

q∈P∖Pr

k(Pr,q)

We have:E[ ∑

△∈Tr∖Tr−1

card(K(△))] ≤ 3(n−1r )E[k(Pr,pr+1)].

But what is k(Pr,pr+1)?

47 / 52

Page 164: Delaunay Triangulations-Part II - Yazdcs.yazd.ac.ir/farshi/Teaching/CG3931/Slides/Delaunay Triangulations... · Review Computing the Delaunay Triangulation Analysis Conclusion Department

ReviewComputing the Delaunay Triangulation

AnalysisConclusion

The Analysis

Any of the remaining n-r points is equally likely to appearas pr+1So:

E[ k(Pr,pr+1)] = 1n−r ∑

q∈P∖Pr

k(Pr,q)

By substitute this into:E[ ∑

△∈Tr∖Tr−1

card(K(△))] ≤ 3r ∑

q∈P∖Pr

k(Pr,q)

We have:E[ ∑

△∈Tr∖Tr−1

card(K(△))] ≤ 3(n−1r )E[k(Pr,pr+1)].

But what is k(Pr,pr+1)?

47 / 52

Page 165: Delaunay Triangulations-Part II - Yazdcs.yazd.ac.ir/farshi/Teaching/CG3931/Slides/Delaunay Triangulations... · Review Computing the Delaunay Triangulation Analysis Conclusion Department

ReviewComputing the Delaunay Triangulation

AnalysisConclusion

The Analysis

Any of the remaining n-r points is equally likely to appearas pr+1So:

E[ k(Pr,pr+1)] = 1n−r ∑

q∈P∖Pr

k(Pr,q)

By substitute this into:E[ ∑

△∈Tr∖Tr−1

card(K(△))] ≤ 3r ∑

q∈P∖Pr

k(Pr,q)

We have:E[ ∑

△∈Tr∖Tr−1

card(K(△))] ≤ 3(n−1r )E[k(Pr,pr+1)].

But what is k(Pr,pr+1)?

47 / 52

Page 166: Delaunay Triangulations-Part II - Yazdcs.yazd.ac.ir/farshi/Teaching/CG3931/Slides/Delaunay Triangulations... · Review Computing the Delaunay Triangulation Analysis Conclusion Department

ReviewComputing the Delaunay Triangulation

AnalysisConclusion

The Analysis

Any of the remaining n-r points is equally likely to appearas pr+1So:

E[ k(Pr,pr+1)] = 1n−r ∑

q∈P∖Pr

k(Pr,q)

By substitute this into:E[ ∑

△∈Tr∖Tr−1

card(K(△))] ≤ 3r ∑

q∈P∖Pr

k(Pr,q)

We have:E[ ∑

△∈Tr∖Tr−1

card(K(△))] ≤ 3(n−1r )E[k(Pr,pr+1)].

But what is k(Pr,pr+1)?

47 / 52

Page 167: Delaunay Triangulations-Part II - Yazdcs.yazd.ac.ir/farshi/Teaching/CG3931/Slides/Delaunay Triangulations... · Review Computing the Delaunay Triangulation Analysis Conclusion Department

ReviewComputing the Delaunay Triangulation

AnalysisConclusion

The Analysis

k(Pr,pr+1),number of triangles of Tr that contain pr+1These are the triangles that will be destroyed when pr+1 isinserted. Theorem 9.6 (i)

Rewrite our sum as:E[ ∑

△∈Tr∖Tr−1

card(K(△))] ≤ 3(n−1r )E[card(Tr∖Tr+1)]

48 / 52

Page 168: Delaunay Triangulations-Part II - Yazdcs.yazd.ac.ir/farshi/Teaching/CG3931/Slides/Delaunay Triangulations... · Review Computing the Delaunay Triangulation Analysis Conclusion Department

ReviewComputing the Delaunay Triangulation

AnalysisConclusion

The Analysis

k(Pr,pr+1),number of triangles of Tr that contain pr+1These are the triangles that will be destroyed when pr+1 isinserted. Theorem 9.6 (i)

Rewrite our sum as:E[ ∑

△∈Tr∖Tr−1

card(K(△))] ≤ 3(n−1r )E[card(Tr∖Tr+1)]

48 / 52

Page 169: Delaunay Triangulations-Part II - Yazdcs.yazd.ac.ir/farshi/Teaching/CG3931/Slides/Delaunay Triangulations... · Review Computing the Delaunay Triangulation Analysis Conclusion Department

ReviewComputing the Delaunay Triangulation

AnalysisConclusion

The Analysis

k(Pr,pr+1),number of triangles of Tr that contain pr+1These are the triangles that will be destroyed when pr+1 isinserted. Theorem 9.6 (i)

Rewrite our sum as:E[ ∑

△∈Tr∖Tr−1

card(K(△))] ≤ 3(n−1r )E[card(Tr∖Tr+1)]

48 / 52

Page 170: Delaunay Triangulations-Part II - Yazdcs.yazd.ac.ir/farshi/Teaching/CG3931/Slides/Delaunay Triangulations... · Review Computing the Delaunay Triangulation Analysis Conclusion Department

ReviewComputing the Delaunay Triangulation

AnalysisConclusion

The Analysis

k(Pr,pr+1),number of triangles of Tr that contain pr+1These are the triangles that will be destroyed when pr+1 isinserted. Theorem 9.6 (i)

Rewrite our sum as:E[ ∑

△∈Tr∖Tr−1

card(K(△))] ≤ 3(n−1r )E[card(Tr∖Tr+1)]

48 / 52

Page 171: Delaunay Triangulations-Part II - Yazdcs.yazd.ac.ir/farshi/Teaching/CG3931/Slides/Delaunay Triangulations... · Review Computing the Delaunay Triangulation Analysis Conclusion Department

ReviewComputing the Delaunay Triangulation

AnalysisConclusion

The Analysis

By Theorem 9.1: Tm has 2(m + 3) - 2 - 3 = 2m + 1Tm+1 has two triangles more than Tm

Thus, card(Tr∖Tr+1)≤ card(triangles destroyed by pr+1)= card(triangles created by pr+1)-2= card(Tr+1∖Tr) - 2We can rewrite our sum as:E[ ∑

△∈Tr∖Tr−1

card(K(△))] ≤ 3(n−1r )(E[card(Tr+1∖Tr)] - 2)

49 / 52

Page 172: Delaunay Triangulations-Part II - Yazdcs.yazd.ac.ir/farshi/Teaching/CG3931/Slides/Delaunay Triangulations... · Review Computing the Delaunay Triangulation Analysis Conclusion Department

ReviewComputing the Delaunay Triangulation

AnalysisConclusion

The Analysis

By Theorem 9.1: Tm has 2(m + 3) - 2 - 3 = 2m + 1Tm+1 has two triangles more than Tm

Thus, card(Tr∖Tr+1)≤ card(triangles destroyed by pr+1)= card(triangles created by pr+1)-2= card(Tr+1∖Tr) - 2We can rewrite our sum as:E[ ∑

△∈Tr∖Tr−1

card(K(△))] ≤ 3(n−1r )(E[card(Tr+1∖Tr)] - 2)

49 / 52

Page 173: Delaunay Triangulations-Part II - Yazdcs.yazd.ac.ir/farshi/Teaching/CG3931/Slides/Delaunay Triangulations... · Review Computing the Delaunay Triangulation Analysis Conclusion Department

ReviewComputing the Delaunay Triangulation

AnalysisConclusion

The Analysis

By Theorem 9.1: Tm has 2(m + 3) - 2 - 3 = 2m + 1Tm+1 has two triangles more than Tm

Thus, card(Tr∖Tr+1)≤ card(triangles destroyed by pr+1)= card(triangles created by pr+1)-2= card(Tr+1∖Tr) - 2We can rewrite our sum as:E[ ∑

△∈Tr∖Tr−1

card(K(△))] ≤ 3(n−1r )(E[card(Tr+1∖Tr)] - 2)

49 / 52

Page 174: Delaunay Triangulations-Part II - Yazdcs.yazd.ac.ir/farshi/Teaching/CG3931/Slides/Delaunay Triangulations... · Review Computing the Delaunay Triangulation Analysis Conclusion Department

ReviewComputing the Delaunay Triangulation

AnalysisConclusion

The Analysis

By Theorem 9.1: Tm has 2(m + 3) - 2 - 3 = 2m + 1Tm+1 has two triangles more than Tm

Thus, card(Tr∖Tr+1)≤ card(triangles destroyed by pr+1)= card(triangles created by pr+1)-2= card(Tr+1∖Tr) - 2We can rewrite our sum as:E[ ∑

△∈Tr∖Tr−1

card(K(△))] ≤ 3(n−1r )(E[card(Tr+1∖Tr)] - 2)

49 / 52

Page 175: Delaunay Triangulations-Part II - Yazdcs.yazd.ac.ir/farshi/Teaching/CG3931/Slides/Delaunay Triangulations... · Review Computing the Delaunay Triangulation Analysis Conclusion Department

ReviewComputing the Delaunay Triangulation

AnalysisConclusion

The Analysis

Remember we fixed Pr earlierConsider all Pr by averaging over both sides of theinequality, but the inequality comes out identical.E[♯ of triangles created by pr]= E[♯ of edges incident to pr+1 in Tr+1]≤ 6Therefore:

E[ ∑△∈Tr∖Tr−1

card(K(△))] ≤ 12(n−1r )

If we sum this over all r, we have shown that:

∑△

card(K(△))= O(nlogn)

And thus, the algorithm runs in O(nlogn) time.50 / 52

Page 176: Delaunay Triangulations-Part II - Yazdcs.yazd.ac.ir/farshi/Teaching/CG3931/Slides/Delaunay Triangulations... · Review Computing the Delaunay Triangulation Analysis Conclusion Department

ReviewComputing the Delaunay Triangulation

AnalysisConclusion

The Analysis

Remember we fixed Pr earlierConsider all Pr by averaging over both sides of theinequality, but the inequality comes out identical.E[♯ of triangles created by pr]= E[♯ of edges incident to pr+1 in Tr+1]≤ 6Therefore:

E[ ∑△∈Tr∖Tr−1

card(K(△))] ≤ 12(n−1r )

If we sum this over all r, we have shown that:

∑△

card(K(△))= O(nlogn)

And thus, the algorithm runs in O(nlogn) time.50 / 52

Page 177: Delaunay Triangulations-Part II - Yazdcs.yazd.ac.ir/farshi/Teaching/CG3931/Slides/Delaunay Triangulations... · Review Computing the Delaunay Triangulation Analysis Conclusion Department

ReviewComputing the Delaunay Triangulation

AnalysisConclusion

The Analysis

Remember we fixed Pr earlierConsider all Pr by averaging over both sides of theinequality, but the inequality comes out identical.E[♯ of triangles created by pr]= E[♯ of edges incident to pr+1 in Tr+1]≤ 6Therefore:

E[ ∑△∈Tr∖Tr−1

card(K(△))] ≤ 12(n−1r )

If we sum this over all r, we have shown that:

∑△

card(K(△))= O(nlogn)

And thus, the algorithm runs in O(nlogn) time.50 / 52

Page 178: Delaunay Triangulations-Part II - Yazdcs.yazd.ac.ir/farshi/Teaching/CG3931/Slides/Delaunay Triangulations... · Review Computing the Delaunay Triangulation Analysis Conclusion Department

ReviewComputing the Delaunay Triangulation

AnalysisConclusion

The Analysis

Remember we fixed Pr earlierConsider all Pr by averaging over both sides of theinequality, but the inequality comes out identical.E[♯ of triangles created by pr]= E[♯ of edges incident to pr+1 in Tr+1]≤ 6Therefore:

E[ ∑△∈Tr∖Tr−1

card(K(△))] ≤ 12(n−1r )

If we sum this over all r, we have shown that:

∑△

card(K(△))= O(nlogn)

And thus, the algorithm runs in O(nlogn) time.50 / 52

Page 179: Delaunay Triangulations-Part II - Yazdcs.yazd.ac.ir/farshi/Teaching/CG3931/Slides/Delaunay Triangulations... · Review Computing the Delaunay Triangulation Analysis Conclusion Department

ReviewComputing the Delaunay Triangulation

AnalysisConclusion

The Analysis

Remember we fixed Pr earlierConsider all Pr by averaging over both sides of theinequality, but the inequality comes out identical.E[♯ of triangles created by pr]= E[♯ of edges incident to pr+1 in Tr+1]≤ 6Therefore:

E[ ∑△∈Tr∖Tr−1

card(K(△))] ≤ 12(n−1r )

If we sum this over all r, we have shown that:

∑△

card(K(△))= O(nlogn)

And thus, the algorithm runs in O(nlogn) time.50 / 52

Page 180: Delaunay Triangulations-Part II - Yazdcs.yazd.ac.ir/farshi/Teaching/CG3931/Slides/Delaunay Triangulations... · Review Computing the Delaunay Triangulation Analysis Conclusion Department

ReviewComputing the Delaunay Triangulation

AnalysisConclusion

The Analysis

Remember we fixed Pr earlierConsider all Pr by averaging over both sides of theinequality, but the inequality comes out identical.E[♯ of triangles created by pr]= E[♯ of edges incident to pr+1 in Tr+1]≤ 6Therefore:

E[ ∑△∈Tr∖Tr−1

card(K(△))] ≤ 12(n−1r )

If we sum this over all r, we have shown that:

∑△

card(K(△))= O(nlogn)

And thus, the algorithm runs in O(nlogn) time.50 / 52

Page 181: Delaunay Triangulations-Part II - Yazdcs.yazd.ac.ir/farshi/Teaching/CG3931/Slides/Delaunay Triangulations... · Review Computing the Delaunay Triangulation Analysis Conclusion Department

ReviewComputing the Delaunay Triangulation

AnalysisConclusion

polyhedral terrain made! ,

51 / 52

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ReviewComputing the Delaunay Triangulation

AnalysisConclusion

52 / 52