## Region-based Approximation Algorithms for Visibility between Imprecise Locations

Let *p* and *q* be two imprecise points, given as probability density functions on ℝ^{2}, and let *R* be a set of *n* line segments in ℝ^{2}. 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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