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Qhull 2003.1 2003/12/30 |
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http://www.qhull.org |
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http://savannah.nongnu.org/projects/qhull/ |
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http://www6.uniovi.es/ftp/pub/mirrors/geom.umn.edu/software/ghindex.html |
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http://www.geomview.org |
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http://www.geom.uiuc.edu |
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Qhull computes convex hulls, Delaunay triangulations, Voronoi diagrams, |
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furthest-site Voronoi diagrams, and halfspace intersections about a point. |
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It runs in 2-d, 3-d, 4-d, or higher. It implements the Quickhull algorithm |
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for computing convex hulls. Qhull handles round-off errors from floating |
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point arithmetic. It can approximate a convex hull. |
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The program includes options for hull volume, facet area, partial hulls, |
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input transformations, randomization, tracing, multiple output formats, and |
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execution statistics. The program can be called from within your application. |
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You can view the results in 2-d, 3-d and 4-d with Geomview. |
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To download Qhull: |
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http://www.qhull.org/download |
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http://savannah.nongnu.org/files/?group=qhull |
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Download qhull-96.ps for: |
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Barber, C. B., D.P. Dobkin, and H.T. Huhdanpaa, "The |
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Quickhull Algorithm for Convex Hulls," ACM Trans. on |
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Mathematical Software, 22(4):469-483, Dec. 1996. |
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http://www.acm.org/pubs/citations/journals/toms/1996-22-4/p469-barber/ |
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http://citeseer.nj.nec.com/83502.html |
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Abstract: |
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The convex hull of a set of points is the smallest convex set that contains |
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the points. This article presents a practical convex hull algorithm that |
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combines the two-dimensional Quickhull Algorithm with the general dimension |
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Beneath-Beyond Algorithm. It is similar to the randomized, incremental |
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algorithms for convex hull and Delaunay triangulation. We provide empirical |
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evidence that the algorithm runs faster when the input contains non-extreme |
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points, and that it uses less memory. |
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Computational geometry algorithms have traditionally assumed that input sets |
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are well behaved. When an algorithm is implemented with floating point |
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arithmetic, this assumption can lead to serious errors. We briefly describe |
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a solution to this problem when computing the convex hull in two, three, or |
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four dimensions. The output is a set of "thick" facets that contain all |
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possible exact convex hulls of the input. A variation is effective in five |
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or more dimensions. |
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