Occluder Simplification Using Planar Sections

We present a method for extreme occluder simplification. We take a triangle soup as input, and produce a small set of polygons with closely matching occlusion properties. In contrast to methods that optimize the original geometry, our algorithm has very few requirements for the input— specifically,...

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Bibliographic Details
Published inComputer graphics forum Vol. 33; no. 1; pp. 235 - 245
Main Authors Silvennoinen, Ari, Saransaari, Hannu, Laine, Samuli, Lehtinen, Jaakko
Format Journal Article
LanguageEnglish
Published Oxford Blackwell Publishing Ltd 01.02.2014
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Summary:We present a method for extreme occluder simplification. We take a triangle soup as input, and produce a small set of polygons with closely matching occlusion properties. In contrast to methods that optimize the original geometry, our algorithm has very few requirements for the input— specifically, the input does not need to be a watertight, two‐manifold mesh. This robustness is achieved by working on a well‐behaved, discretized representation of the input instead of the original, potentially badly structured geometry. We first formulate the algorithm for individual occluders, and further introduce a hierarchy for handling large, complex scenes. We present a method for extreme occluder simplification. We take a triangle soup as input, and produce a small set of polygons with closely matching occlusion properties. In contrast to methods that optimize the original geometry, our algorithm has very few requirements for the input— specifically, the input does not need to be a watertight, two‐manifold mesh. This robustness is achieved by working on a well‐behaved, discretized representation of the input instead of the original, potentially badly structured geometry. We first formulate the algorithm for individual occluders, and further introduce a hierarchy for handling large, complex scenes.
Bibliography:istex:0350821855FACCE391BF31DDC94E6CF4535AEE2E
ArticleID:CGF12271
ark:/67375/WNG-5B2F7BD3-L
ISSN:0167-7055
1467-8659
DOI:10.1111/cgf.12271