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The algorithm will always correctly determine the closest pair, because it maps any pair closer than distance to the same grid point or to adjacent grid points. The uniform sampling of pairs in the first step of the algorithm (compared to a different method of Rabin for sampling a similar number of pairs) simplifies the proof that the expected ...
The closest pair of points corresponds to two adjacent cells in the Voronoi diagram. If the setting is the Euclidean plane and a discrete set of points is given, then two points of the set are adjacent on the convex hull if and only if their Voronoi cells share an infinitely long side.
Formally, the nearest-neighbor (NN) search problem is defined as follows: given a set S of points in a space M and a query point q ∈ M, find the closest point in S to q. Donald Knuth in vol. 3 of The Art of Computer Programming (1973) called it the post-office problem, referring to an application of assigning to a residence the nearest post ...
Proximity problems is a class of problems in computational geometry which involve estimation of distances between geometric objects.. A subset of these problems stated in terms of points only are sometimes referred to as closest point problems, [1] although the term "closest point problem" is also used synonymously to the nearest neighbor search.
Closest pair problem: find the pair of points (from a set of points) with the smallest distance between them; Collision detection algorithms: check for the collision or intersection of two given solids; Cone algorithm: identify surface points; Convex hull algorithms: determining the convex hull of a set of points Graham scan; Quickhull
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For a given set of points in space, a Voronoi diagram is a decomposition of space into cells, one for each given point, so that anywhere in space, the closest given point is inside the cell. This is equivalent to nearest neighbor interpolation, by assigning the function value at the given point to all the points inside the cell. [3]
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