Nearest Neighbour Search for Visualization Using Arbitrary Triangulations

  • Frank Weller
  • Robert Mencl
Part of the Eurographics book series (EUROGRAPH)


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.


Convex Hull Hash Table Delaunay Triangulation Distance Computation Query Point 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag/Wien 1996

Authors and Affiliations

  • Frank Weller
    • 1
  • Robert Mencl
    • 1
  1. 1.Informatik VII (Computer Graphics)Universität DortmundDortmundGermany

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