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Published in: Journal of Visualization 5/2022

12-05-2022 | Regular Paper

Compact tetrahedralization-based acceleration structures for ray tracing

Authors: Aytek Aman, Serkan Demirci, Uğur Güdükbay

Published in: Journal of Visualization | Issue 5/2022

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Abstract

We propose compact and efficient tetrahedral mesh representations to improve the ray-tracing performance. We reorder tetrahedral mesh data using a space-filling curve to improve cache locality. Most importantly, we propose efficient ray-traversal algorithms. We provide details of the regular ray-tracing operations on tetrahedral meshes and the GPU implementation of our traversal method. We demonstrate our findings through a set of comprehensive experiments. Our method outperforms existing tetrahedral mesh-based traversal methods and yields comparable results to the traversal methods based on the state-of-the-art acceleration structures such as k-dimensional (k-d) tree and Bounding Volume Hierarchy (BVH) in terms of speed. Storage-wise, our method uses less memory than its tetrahedral mesh-based counterparts, thus allowing larger scenes to be rendered on the GPU.

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Appendix
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Metadata
Title
Compact tetrahedralization-based acceleration structures for ray tracing
Authors
Aytek Aman
Serkan Demirci
Uğur Güdükbay
Publication date
12-05-2022
Publisher
Springer Berlin Heidelberg
Published in
Journal of Visualization / Issue 5/2022
Print ISSN: 1343-8875
Electronic ISSN: 1875-8975
DOI
https://doi.org/10.1007/s12650-022-00842-x

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