Constrained Delaunay triangulation

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In computational geometry, a constrained Delaunay triangulation is a generalization of the Delaunay triangulation that forces certain required segments into the triangulation as edges, [1] [2] unlike the Delaunay triangulation itself which is based purely on the position of a given set of vertices without regard to how they should be connected by edges. It can be computed efficiently and has applications in geographic information systems and in mesh generation.

Contents

Definition

The input to the constrained Delaunay triangulation problem is a planar straight-line graph, a set of points and non-crossing line segments in the plane. The constrained Delaunay triangulation of this input is a triangulation of its convex hull, including all of the input segments as edges, and using only the vertices of the input. For every additional edge added to this input to make it into a triangulation, there should exist a circle through the endpoints of , such that any vertex interior to the circle is blocked from visibility from at least one endpoint of by a segment of the input. This generalizes the defining property of two-dimensional Delaunay triangulations of points, that each edge have a circle through its two endpoints containing no other vertices. A triangulation satisfying these properties always exists. [1]

Jonathan Shewchuk has generalized this definition to constrained Delaunay triangulations of three-dimensional inputs, systems of points and non-crossing segments and triangles in three-dimensional space; however, not every input of this type has a constrained Delaunay triangulation according to his generalized definition. [2]

Algorithms

Several algorithms for computing constrained Delaunay triangulations of planar straight-line graphs in time are known. [1] [3] The constrained Delaunay triangulation of a simple polygon can be constructed in linear time. [4]

Applications

In topographic surveying, one constructs a triangulation from points shot in the field. If an edge of the triangulation crosses a river, the resulting surface does not accurately model the path of the river. So one draws breaklines along rivers, edges of roads, mountain ridges, and the like. The breaklines are used as constraints when constructing the triangulation.

Constrained Delaunay triangulation can also be used in Delaunay refinement methods for mesh generation, as a way to force the mesh to conform with the domain boundaries as it is being refined.

Related Research Articles

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Polygon triangulation

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Euclidean minimum spanning tree

The Euclidean minimum spanning tree or EMST is a minimum spanning tree of a set of points in the plane or higher-dimensional Euclidean space. It connects the points by a system of line segments, so that any two points can reach each other along a path through the line segments, and it selects line segments that minimize the sum of the Euclidean distances between directly-connected pairs of points.

Point-set triangulation

A triangulation of a set of points in the Euclidean space is a simplicial complex that covers the convex hull of , and whose vertices belong to . In the plane, triangulations are made up of triangles, together with their edges and vertices. Some authors require that all the points of are vertices of its triangulations. In this case, a triangulation of a set of points in the plane can alternatively be defined as a maximal set of non-crossing edges between points of . In the plane, triangulations are special cases of planar straight-line graphs.

In geometry, a triangulation is a subdivision of a planar object into triangles, and by extension the subdivision of a higher-dimension geometric object into simplices. Triangulations of a three-dimensional volume would involve subdividing it into tetrahedra packed together.

Dual graph Graph representing faces of another graph

In the mathematical discipline of graph theory, the dual graph of a plane graph G is a graph that has a vertex for each face of G. The dual graph has an edge for each pair of faces in G that are separated from each other by an edge, and a self-loop when the same face appears on both sides of an edge. Thus, each edge e of G has a corresponding dual edge, whose endpoints are the dual vertices corresponding to the faces on either side of e. The definition of the dual depends on the choice of embedding of the graph G, so it is a property of plane graphs rather than planar graphs. For planar graphs generally, there may be multiple dual graphs, depending on the choice of planar embedding of the graph.

Triangulated irregular network

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Mesh generation is the practice of creating a mesh, a subdivision of a continuous geometric space into discrete geometric and topological cells. Often these cells form a simplicial complex. Usually the cells partition the geometric input domain. Mesh cells are used as discrete local approximations of the larger domain. Meshes are created by computer algorithms, often with human guidance through a GUI, depending on the complexity of the domain and the type of mesh desired. A typical goal is to create a mesh that accurately captures the input domain geometry, with high-quality (well-shaped) cells, and without so many cells as to make subsequent calculations intractable. The mesh should also be fine in areas that are important for the subsequent calculations.

Geometric graph theory

Geometric graph theory in the broader sense is a large and amorphous subfield of graph theory, concerned with graphs defined by geometric means. In a stricter sense, geometric graph theory studies combinatorial and geometric properties of geometric graphs, meaning graphs drawn in the Euclidean plane with possibly intersecting straight-line edges, and topological graphs, where the edges are allowed to be arbitrary continuous curves connecting the vertices, thus it is "the theory of geometric and topological graphs". Geometric graphs are also known as spatial networks.

Pseudotriangle

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Planar straight-line graph

In computational geometry and geometric graph theory, a planar straight-line graph, in short PSLG, is a term used for an embedding of a planar graph in the plane such that its edges are mapped into straight-line segments. Fáry's theorem (1948) states that every planar graph has this kind of embedding.

Polygonal chain

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Relative neighborhood graph

In computational geometry, the relative neighborhood graph (RNG) is an undirected graph defined on a set of points in the Euclidean plane by connecting two points and by an edge whenever there does not exist a third point that is closer to both and than they are to each other. This graph was proposed by Godfried Toussaint in 1980 as a way of defining a structure from a set of points that would match human perceptions of the shape of the set.

In mesh generation, Delaunay refinement are algorithms for mesh generation based on the principle of adding Steiner points to the geometry of an input to be meshed, in a way that causes the Delaunay triangulation or constrained Delaunay triangulation of the augmented input to meet the quality requirements of the meshing application. Delaunay refinement methods include methods by Chew and by Ruppert.

In polyhedral combinatorics, a branch of mathematics, Steinitz's theorem is a characterization of the undirected graphs formed by the edges and vertices of three-dimensional convex polyhedra: they are exactly the 3-vertex-connected planar graphs. That is, every convex polyhedron forms a 3-connected planar graph, and every 3-connected planar graph can be represented as the graph of a convex polyhedron. For this reason, the 3-connected planar graphs are also known as polyhedral graphs.

In computational geometry and computer science, the minimum-weight triangulation problem is the problem of finding a triangulation of minimal total edge length. That is, an input polygon or the convex hull of an input point set must be subdivided into triangles that meet edge-to-edge and vertex-to-vertex, in such a way as to minimize the sum of the perimeters of the triangles. The problem is NP-hard for point set inputs, but may be approximated to any desired degree of accuracy. For polygon inputs, it may be solved exactly in polynomial time. The minimum weight triangulation has also sometimes been called the optimal triangulation.

Local feature size

Local feature size refers to several related concepts in computer graphics and computational geometry for measuring the size of a geometric object near a particular point.

In graph drawing and geometric graph theory, a Tutte embedding or barycentric embedding of a simple 3-vertex-connected planar graph is a crossing-free straight-line embedding with the properties that the outer face is a convex polygon and that each interior vertex is at the average of its neighbors' positions. If the outer polygon is fixed, this condition on the interior vertices determines their position uniquely as the solution to a system of linear equations. Solving the equations geometrically produces a planar embedding. Tutte's spring theorem, proven by W. T. Tutte (1963), states that this unique solution is always crossing-free, and more strongly that every face of the resulting planar embedding is convex. It is called the spring theorem because such an embedding can be found as the equilibrium position for a system of springs representing the edges of the graph.

References

  1. 1 2 3 Chew, L. Paul (1989), "Constrained Delaunay triangulations", Algorithmica , 4 (1): 97–108, doi:10.1007/BF01553881, MR   0983658, S2CID   189918468
  2. 1 2 Shewchuk, Jonathan Richard (2008), "General-dimensional constrained Delaunay and constrained regular triangulations. I. Combinatorial properties", Discrete & Computational Geometry , 39 (1–3): 580–637, doi: 10.1007/s00454-008-9060-3 , MR   2383774
  3. Wang, Cao An; Schubert, Lenhart K. (1987), "An optimal algorithm for constructing the Delaunay triangulation of a set of line segments", in Soule, D. (ed.), Proceedings of the Third Annual Symposium on Computational Geometry, Waterloo, Ontario, Canada, June 8-10, 1987, ACM, pp. 223–232, doi:10.1145/41958.41982, S2CID   18490297
  4. Chin, Francis; Wang, Cao An (1999), "Finding the constrained Delaunay triangulation and constrained Voronoi diagram of a simple polygon in linear time", SIAM Journal on Computing , 28 (2): 471–486, doi:10.1137/S0097539795285916, hdl: 10722/47094 , MR   1634357