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The skip quadtree: a simple dynamic data structure for multidimensional data

Published: 06 June 2005 Publication History

Abstract

We present a new multi-dimensional data structure, which we call the skip quadtree (for point data in R2) or the skip octree (for point data in Rd, with constant d > 2). Our data structure combines the best features of two well-known data structures, in that it has the well-defined "box"-shaped regions of region quadtrees and the logarithmic-height search and update hierarchical structure of skip lists. Indeed, the bottom level of our structure is exactly a region quadtree (or octree for higher dimensional data). We describe efficient algorithms for inserting and deleting points in a skip quadtree, as well as fast methods for performing point location, approximate range, and approximate nearest neighbor queries.

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cover image ACM Conferences
SCG '05: Proceedings of the twenty-first annual symposium on Computational geometry
June 2005
398 pages
ISBN:1581139918
DOI:10.1145/1064092
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 06 June 2005

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Author Tags

  1. approximation algorithm
  2. dynamic data structure
  3. nearest neighbor
  4. octree
  5. point location
  6. quadtree
  7. range
  8. skip quadtree

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SCG '05 Paper Acceptance Rate 41 of 141 submissions, 29%;
Overall Acceptance Rate 625 of 1,685 submissions, 37%

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