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An Approximation Algorithm for Computing the Visibility Region of a Point on a Terrain and Visibility Testing.

Authors: Alipour, S.; Ghodsi, M.; Güdükbay, Uğur; Golkari, M.;

An Approximation Algorithm for Computing the Visibility Region of a Point on a Terrain and Visibility Testing.

Abstract

Date of Conference: 5-8 Jan. 2014 Conference name: 2014 International Conference on Computer Vision Theory and Applications (VISAPP) Given a terrain and a query point p on or above it, we want to count the number of triangles of terrain that are visible from p. We present an approximation algorithm to solve this problem. We implement the algorithm and then we run it on the real data sets. The experimental results show that our approximation solution is very close to the real solution and compare to the other similar works, the running time of our algorithm is better than their algorithm. The analysis of time complexity of algorithm is also presented. Also, we consider visibility testing problem, where the goal is to test whether p and a given triangle of train are visible or not. We propose an algorithm for this problem and show that the average running time of this algorithm will be the same as running time of the case where we want to test the visibility between two query point p and q.

Country
Turkey
Related Organizations
Keywords

Average running time, Landforms, Problem solving, Real solutions, Real data sets, Approximation algorithm, Running time, Computational geometry, Approximation algorithms, Computational complexity, Time complexity, Number of triangles, Approximation solution, Visibility, Terrain

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average