8 research outputs found

    Distance-Sensitive Planar Point Location

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    Let S\mathcal{S} be a connected planar polygonal subdivision with nn edges that we want to preprocess for point-location queries, and where we are given the probability γi\gamma_i that the query point lies in a polygon PiP_i of S\mathcal{S}. We show how to preprocess S\mathcal{S} such that the query time for a point~pPip\in P_i depends on~γi\gamma_i and, in addition, on the distance from pp to the boundary of~PiP_i---the further away from the boundary, the faster the query. More precisely, we show that a point-location query can be answered in time O(min(logn,1+logarea(Pi)γiΔp2))O\left(\min \left(\log n, 1 + \log \frac{\mathrm{area}(P_i)}{\gamma_i \Delta_{p}^2}\right)\right), where Δp\Delta_{p} is the shortest Euclidean distance of the query point~pp to the boundary of PiP_i. Our structure uses O(n)O(n) space and O(nlogn)O(n \log n) preprocessing time. It is based on a decomposition of the regions of S\mathcal{S} into convex quadrilaterals and triangles with the following property: for any point pPip\in P_i, the quadrilateral or triangle containing~pp has area Ω(Δp2)\Omega(\Delta_{p}^2). For the special case where S\mathcal{S} is a subdivision of the unit square and γi=area(Pi)\gamma_i=\mathrm{area}(P_i), we present a simpler solution that achieves a query time of O(min(logn,log1Δp2))O\left(\min \left(\log n, \log \frac{1}{\Delta_{p}^2}\right)\right). The latter solution can be extended to convex subdivisions in three dimensions

    Allocation of kidney transplants in the UK

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