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Region-Based Approximation of Probability Distributions (for Visibility Between Imprecise Points Among Obstacles)

机译:基于区域的概率分布近似值(障碍物之间的不精确点之间的可见性)

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Let p and q be two imprecise points, given as probability density functions on R2, and let O be a set of disjoint polygonal obstacles in R2. We study the problem of approximating the probability that p and q can see each other; i.e., that the segment connecting p and q does not cross any obstacle in O. To solve this problem, we first approximate each density function by a weighted set of polygons. Then we focus on computing the visibility between two points inside two of such polygons, where we can assume that the points are drawn uniformly at random. We show how this problem can be solved exactly in O((n+m)2) time, where n and m are the total complexities of the two polygons and the set of obstacles, respectively. Using this as a subroutine, we show that the probability that p and q can see each other amidst a set of obstacles of total complexity m can be approximated within error epsilon in O(1/epsilon 3+m2/epsilon 2) time.
机译:让P和Q是r2上的概率密度函数给出的两个不精确点,让O在R2中是一组不相交的多边形障碍物。我们研究了近似P和Q可以互相看到的概率的问题;即,连接P和Q的段不会在O中跨越任何障碍。为了解决这个问题,我们首先将每个密度函数近似于加权的多边形。然后,我们专注于计算两个这样的多边形内部两个点之间的可见性,在那里我们可以假设该点随机均匀地绘制。我们展示了这个问题如何完全解决O((n + m)2)时间,其中n和m分别是两个多边形和障碍物集的总复杂性。使用这作为子程序,我们表明P和Q可以在总复杂性M的一组障碍中看到彼此的概率可以在O(1 / epsilon 3 + M2 / epsilon 2)时间内的错误epsilon内近似。

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