Parallel and Scalable Heat Methods for Geodesic Distance Computation

In this paper, we propose a parallel and scalable approach for geodesic distance computation on triangle meshes. Our key observation is that the recovery of geodesic distance with the heat method <xref ref-type="bibr" rid="ref1">[1] can be reformulated as optimization of it...

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Vydané v:	IEEE transactions on pattern analysis and machine intelligence Ročník 43; číslo 2; s. 579 - 594
Hlavní autori:	Tao, Jiong, Zhang, Juyong, Deng, Bailin, Fang, Zheng, Peng, Yue, He, Ying
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	United States IEEE 01.02.2021 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:	Apexes Approximation algorithms Computation Computational modeling heat diffusion Heat method Heat recovery Linear systems Memory management Optimization parallel algorithm Parallel processing poisson equation Random access memory scalability Solvers
ISSN:	0162-8828, 1939-3539, 2160-9292, 1939-3539
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