The.Algorithm.Design.Manual.Springer-Verlag.1998
The.Algorithm.Design.Manual.Springer-Verlag.1998 The.Algorithm.Design.Manual.Springer-Verlag.1998
Convex Hull Dynamic algorithms for convex-hull maintenance are data structures that permit inserting and deleting arbitrary points while always representing the current convex hull. The first such dynamic data structure [OvL81] supported insertions and deletions in time. Expositions of this result include [PS85]. Related Problems: Sorting (see page ), Voronoi diagrams (see page ). Next: Triangulation Up: Computational Geometry Previous: Robust Geometric Primitives Algorithms Mon Jun 2 23:33:50 EDT 1997 file:///E|/BOOK/BOOK4/NODE185.HTM (5 of 5) [19/1/2003 1:31:37]
Triangulation Next: Voronoi Diagrams Up: Computational Geometry Previous: Convex Hull Triangulation Input description: A set of points or a polyhedon. Problem description: Partition the interior of the point set or polyhedron into triangles. Discussion: Triangulation is a fundamental problem in computational geometry, because the first step in working with complicated geometric objects is to break them into simple geometric objects. The simplest geometric objects are triangles in two dimensions, and tetrahedra in three. Classical applications of triangulation include finite element analysis and computer graphics. A particularly interesting application of triangulation is surface or function interpolation. Suppose that we have sampled the height of a mountain at a certain number of points. How can we estimate the height at any point q in the plane? If we project the points on the plane, and then triangulate them, the triangulation completely partitions the plane into regions. We can estimate the height of q by interpolating among the three points of the triangle that contains it. Further, this triangulation and the associated height values define a surface of the mountain suitable for graphics rendering. In the plane, a triangulation is constructed by adding nonintersecting chords between the vertices until no more such chords can be added. Specific issues arising in triangulation include: file:///E|/BOOK/BOOK4/NODE186.HTM (1 of 4) [19/1/2003 1:31:39]
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Triangulation<br />
Next: Voronoi Diagrams Up: Computational Geometry Previous: Convex Hull<br />
Triangulation<br />
Input description: A set of points or a polyhedon.<br />
Problem description: Partition the interior of the point set or polyhedron into triangles.<br />
Discussion: Triangulation is a fundamental problem in computational geometry, because the first step in<br />
working with complicated geometric objects is to break them into simple geometric objects. <strong>The</strong> simplest<br />
geometric objects are triangles in two dimensions, and tetrahedra in three. Classical applications of<br />
triangulation include finite element analysis and computer graphics.<br />
A particularly interesting application of triangulation is surface or function interpolation. Suppose that<br />
we have sampled the height of a mountain at a certain number of points. How can we estimate the height<br />
at any point q in the plane? If we project the points on the plane, and then triangulate them, the<br />
triangulation completely partitions the plane into regions. We can estimate the height of q by interpolating<br />
among the three points of the triangle that contains it. Further, this triangulation and the associated height<br />
values define a surface of the mountain suitable for graphics rendering.<br />
In the plane, a triangulation is constructed by adding nonintersecting chords between the vertices until no<br />
more such chords can be added. Specific issues arising in triangulation include:<br />
file:///E|/BOOK/BOOK4/NODE186.HTM (1 of 4) [19/1/2003 1:31:39]