7 research outputs found
Overlap of convex polytopes under rigid motion
We present an algorithm to compute a rigid motion that approximately maximizes the volume of the intersection of two convex polytopes P-1 and P-2 in R-3. For all epsilon is an element of (0, 1/2] and for all n >= 1/epsilon, our algorithm runs in O(epsilon(-3) n log(3.5) n) time with probability 1 - n(-O(1)). The volume of the intersection guaranteed by the output rigid motion is a (1 - epsilon)-approximation of the optimum, provided that the optimum is at least lambda . max{vertical bar P-1 vertical bar . vertical bar P-2 vertical bar} for some given constant lambda is an element of (0, 1]. (C) 2013 Elsevier B.V. All rights reserved.X1155Ysciescopu
Approximating the Maximum Overlap of Polygons under Translation
Let and be two simple polygons in the plane of total complexity ,
each of which can be decomposed into at most convex parts. We present an
-approximation algorithm, for finding the translation of ,
which maximizes its area of overlap with . Our algorithm runs in
time, where is a constant that depends only on and .
This suggest that for polygons that are "close" to being convex, the problem
can be solved (approximately), in near linear time
Overlap of Convex Polytopes under Rigid Motion ∗
We present an algorithm to compute an approximate overlap of two convex polytopes P1 and P2 in R 3 under rigid motion. Given any ε ∈ (0, 1/2], our algorithm runs in O(ε −3 n log 3.5 n) time with probability 1 − n −O(1) and returns a (1 − ε)-approximate maximum overlap, provided that the maximum overlap is at least λ · max{|P1|, |P2|} for some given constant λ ∈ (0, 1]
Overlap of convex polytopes under rigid motion
We present an algorithm to compute an approximate overlap of two convex polytopes P1 and P2 in R under rigid motion. Given any ε ∈ (0,1/2], our algorithm runs in O(ε-3 n log 3.5 n) time with probability 1 - n-O(1) and returns a (1 - ε) -approximate maximum overlap, provided that the maximum overlap is at least λ · max{\P1\, \P2\} for some given constant λ ∈ (0,1]. © H.-K. Ahn, S.-W. Cheng, H.J. Kwon, and J. Yon