Pattern matching for spatial point sets

David E. Cardoze, L. Schulman
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引用次数: 70

Abstract

Two sets of points in d-dimensional space are given: a data set D consisting of N points, and a pattern set or probe P consisting of k points. We address the problem of determining whether there is a transformation, among a specified group of transformations of the space, carrying P into or near (meaning at a small directed Hausdorff distance of) D. The groups we consider are translations and rigid motions. Runtimes of approximately O(nlogn) and O(n/sup d/logn) respectively are obtained (letting n=max{N,k} and omitting the effects of several secondary parameters). For translations, a runtime of approximately O(n(ak+1)log/sup 2/n) is obtained for the case that a constant fraction /spl alpha/<1 of the points of the probe is allowed to fail to match.
空间点集的模式匹配
给出了D维空间中的两组点:由N个点组成的数据集D和由k个点组成的模式集或探针P。我们解决的问题是,在空间的一组特定变换中,是否存在一个变换,使P进入或接近d(意思是在一个小的有向豪斯多夫距离)。我们考虑的组是平移和刚性运动。得到的运行时间分别约为O(nlogn)和O(n/sup d/logn)(让n=max{n,k}并忽略几个次要参数的影响)。对于平移,在允许探针点的常数分数/spl alpha/<1无法匹配的情况下,可以获得大约O(n(ak+1)log/sup 2/n)的运行时间。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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