Abstract
A fast and exact algorithm for computing the k-nearest neighbours, or k-closest points in terms of Euclidean distance, for all data in three-dimensional point clouds is presented that avoids using complicated Voronoi diagrams or Dirichlet tessellations. Experimental evidence suggests that the algorithm has a timing of O(n) for most practical values of k under the condition: k <0.05n, where n is the number of three-dimensional points in the cloud. Case studies are presented to illustrate the robustness and efficiency of the method and a comparison is made to an existing exact method.
Original language | English |
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Pages (from-to) | 1467-1472 |
Number of pages | 6 |
Journal | Proceedings of the Institution of Mechanical Engineers Part B Journal of Engineering Manufacture |
Volume | 221 |
Issue number | 9 |
DOIs | |
Publication status | Published - 1 Jan 2007 |
Keywords
- reverse engineering
- three-dimensional scattered point data
- k-nearest neighbours