“…When d = 3 there exist some fast algorithms for projecting onto polyhedra [21,24,25] that can be used in (10). This expression needs to project all the vertices of both polytopes.…”
Section: An Expression For Computing the Hausdorff Distance Between Pmentioning
confidence: 99%
“…We call HERC to an algorithm for computing the Hausdorff distance between polyhedra, based on (10) and on the following techniques • Local Search Algorithm Based on Faces (LSABF) [24,25], for finding the projections which appear in (10). • Exterior Random Covering (ERC) for computing the maximum distance.…”
Section: An Expression For Computing the Hausdorff Distance Between Pmentioning
In this paper, a simple yet efficient randomized algorithm (Exterior Random Covering) for finding the maximum distance from a point set to an arbitrary compact set in R d is presented. This algorithm can be used for accelerating the computation of the Hausdorff distance between complex polytopes.
“…When d = 3 there exist some fast algorithms for projecting onto polyhedra [21,24,25] that can be used in (10). This expression needs to project all the vertices of both polytopes.…”
Section: An Expression For Computing the Hausdorff Distance Between Pmentioning
confidence: 99%
“…We call HERC to an algorithm for computing the Hausdorff distance between polyhedra, based on (10) and on the following techniques • Local Search Algorithm Based on Faces (LSABF) [24,25], for finding the projections which appear in (10). • Exterior Random Covering (ERC) for computing the maximum distance.…”
Section: An Expression For Computing the Hausdorff Distance Between Pmentioning
In this paper, a simple yet efficient randomized algorithm (Exterior Random Covering) for finding the maximum distance from a point set to an arbitrary compact set in R d is presented. This algorithm can be used for accelerating the computation of the Hausdorff distance between complex polytopes.
“…It also describes some global properties of the directions whose corresponding rays intersect the polyhedron. Proof (i) See [16]. (ii) Follows from (i) and the convexity of P.…”
Section: Local Search Algorithm Based On Visibilitymentioning
confidence: 95%
“…Local search strategies provide a fast way of solving some geometric optimization problems [5,6,10,[15][16][17]. For solving the RCPI problem, we can determine a starting face and a way to go from a face to the next one, until arriving at a decision face.…”
Section: Contribution and Organization Of The Papermentioning
confidence: 99%
“…If p is far enough from P (1) is fulfilled. Below we give the C-like pseudocode of an algorithm based on the above proposition, see [16].…”
Section: Then There Exists An Oriented Face (A N) ∈ F (P) Such That mentioning
In this paper we present a new algorithm (LSABV) for determining the intersection between a ray and a convex polyhedron (RCPI) in a fast way. LSABV is based on local search and the concept of visibility. LSABV requires only the boundary description of the polyhedron and it does not need additional data structures. Numerical experiments show that LSABV is faster than Haines's algorithm in the case of polyhedra with moderate or large number of faces.
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