1999
DOI: 10.1016/s0925-7721(98)00035-2
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Fast randomized point location without preprocessing in two- and three-dimensional Delaunay triangulations

Abstract: This paper studies the point location problem in Delaunay triangulations without preprocessing and additional storage. The proposed procedure finds the query point by simply "walking through" the triangulation, after selecting a "good starting point" by random sampling. The analysis generalizes and extends a recent result for d = 2 dimensions by proving this procedure takes expected time close to O(n 1/(d+1)) for point location in Delaunay triangulations of n random points in d = 3 dimensions. Empirical result… Show more

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Cited by 66 publications
(65 citation statements)
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“…This "point location problem", which is a standard problem in geographic information systems and computer-aided design and engineering [74], is the most time consuming part. However, the number of tagged elements (which are cut by the slice plane) is usually far smaller than the total number of elements, and so we can use a brute force yet clever approach, which takes advantage of some peculiarities of our specific problem.…”
Section: Data Outputmentioning
confidence: 99%
“…This "point location problem", which is a standard problem in geographic information systems and computer-aided design and engineering [74], is the most time consuming part. However, the number of tagged elements (which are cut by the slice plane) is usually far smaller than the total number of elements, and so we can use a brute force yet clever approach, which takes advantage of some peculiarities of our specific problem.…”
Section: Data Outputmentioning
confidence: 99%
“…The first application is the randomized incremental construction of the Delaunay Triangulation using the Jump-andWalk strategy, introduced by Mücke, Zhu et al [12], [13]. This strategy proceeds in an incremental way.…”
Section: Convex Hull (2d-hull) and The Construction Of The Twodimensmentioning
confidence: 99%
“…To know the value of a given attribute at a location x, one simply has to find the cell containing x- Mücke et al (1999) describe an efficient way to achieving that.…”
Section: Spatial Interpolationmentioning
confidence: 99%