Region-based Approximation Algorithms for Visibility between Imprecise Locations
Let p and q be two imprecise points, given as probability density functions on ℝ2, and let R be a set of n line segments in ℝ2. We approximate the probability that p and q can see each other; that is, that the segment connecting p and q does not cross any segment of R. To solve this problem, we approximate each density function by a weighted set of polygons; a novel approach to dealing with probability density functions in computational geometry.
keywords: Computational Geometry, Geographical Information Analysis, Data Imprecision
Conference Proceedings (peer-reviewed)
Irina Kostitsyna, Kevin Buchin, Maarten Löffler, Rodrigo I. Silveira
Region-based Approximation Algorithms for Visibility between Imprecise Locations
Proc. 30th Meeting on Algorithm Engineering & Experiments
94–103, 2015
Workshop or Poster (weakly reviewed)
Irina Kostitsyna, Kevin Buchin, Maarten Löffler, Rodrigo I. Silveira
Region-based approximation of probability distributions (for visibility between imprecise points among obstacles)
Proc. 30th European Workshop on Computational Geometry
, 2014
Archived Publication (not reviewed)
Irina Kostitsyna, Kevin Buchin, Maarten Löffler, Rodrigo I. Silveira
Region-based approximation of probability distributions (for visibility between imprecise points among obstacles)
1402.5681, 2014
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