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Link distance and shortest path problems in the plane

机译:平面中的链接距离和最短路径问题

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This paper describes algorithms to compute Voronoi diagrams, shortest path maps, the Hausdorff distance, and the Fréchet distance in the plane with polygonal obstacles. The underlying distance measures for these algorithms are either shortest path distances or link distances. The link distance between a pair of points is the minimum number of edges needed to connect the two points with a polygonal path that avoids a set of obstacles. The motivation for minimizing the number of edges on a path comes from robotic motions and wireless communications because turns are more difficult in these settings than straight movements. Link-based Voronoi diagrams are different from traditional Voronoi diagrams because a query point in the interior of a Voronoi face can have multiple nearest sites. Our site-based Voronoi diagram ensures that all points in a face have the same set of nearest sites. Our distance-based Voronoi diagram ensures that all points in a face have the same distance to a nearest site. The shortest path maps in this paper support queries from any source point on a fixed line segment. This is a middle-ground approach because traditional shortest path maps typically support queries from either a fixed point or from all possible points in the plane. The Hausdorff distance and Fréchet distance are fundamental similarity metrics for shape matching. This paper shows how to compute new variations of these metrics using shortest paths or link-based paths that avoid polygonal obstacles in the plane.
机译:本文介绍了在具有多边形障碍物的平面中计算Voronoi图,最短路径图,Hausdorff距离和Fréchet距离的算法。这些算法的基本距离度量是最短路径距离或链接距离。一对点之间的链接距离是将两个点与避免一组障碍的多边形路径连接所需的最小边数。减少路径上的边沿数量的动机来自机器人运动和无线通信,因为在这些设置中转弯比直线运动更困难。基于链接的Voronoi图与传统Voronoi图不同,因为Voronoi面内部的查询点可以具有多个最近的站点。我们基于站点的Voronoi图可确保面上的所有点都具有相同的一组最近站点。我们基于距离的Voronoi图确保了脸部所有点到最近地点的距离相同。本文中的最短路径图支持从固定线段上的任何源点进行查询。这是一种中间立场的方法,因为传统的最短路径图通常支持从固定点或平面中所有可能点的查询。 Hausdorff距离和Fréchet距离是形状匹配的基本相似性度量。本文展示了如何使用最短路径或基于链接的路径来计算平面中的多边形障碍物,以计算这些度量的新变化。

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