Nearest Neighbour Search for Visualization Using Arbitrary Triangulations
In visualization of scattered data, one is often faced with the problem of finding the nearest neighbours of a data site. This task frequently occurs in an advanced stage of the visualization process, where several data structures have been created during run time. Many applications compute a triangulation of the data for their visualization purposes. To take advantage of this previously allocated data structure we propose an algorithm for determining the k nearest neighbours in a triangulated point set. As a benefit, this algorithm dynamically computes exactly as many neighbours as necessary for the specific application and does not assume a particular kind of triangulation. Furthermore, it works in any finite-dimensional, metric affine space.
KeywordsConvex Hull Hash Table Delaunay Triangulation Distance Computation Query Point
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