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Progressive Parameterizations

delete2018-07-30
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刘利刚 cover
刘利刚 (Ligang Liu)
叶
叶春杨 (Chunyang Ye)
X
Xiao‐Ming Fu *
DOI:10.1145/3197517.3201331delete
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Abstract

Abstract

En 中文
We propose a novel approach, called Progressive Parameterizations, to compute foldover-free parameterizations with low isometric distortion on disk topology meshes. Instead of using the input mesh as a reference to define the objective function, we introduce a progressive reference that contains bounded distortion to the parameterized mesh and is as close as possible to the input mesh. After optimizing the bounded distortion energy between the progressive reference and the parameterized mesh, the parameterized mesh easily approaches the progressive reference, thereby also coming close to the input. By iteratively generating the progressive reference and optimizing the bounded distortion energy to update the parameterized mesh, our algorithm achieves high-quality parameterizations with strong practical reliability and high efficiency. We have demonstrated that our algorithm succeeds on a massive test data set containing over 20712 complex disk topology meshes. Compared to the state-of-the-art methods, our method has achieved higher computational efficiency and practical reliability.
Keywords:
parameterizations
isometric mapping
low distortion
foldover-free
flip-free
AI Summary

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Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.

Journal

ACM Transactions on Graphics cover
ACM Transactions on Graphics
IF:
9.5
Papers:
4.8K
Citations:
3.6W

Organization

C
chinese academy of sciences
Scholars:
56.7W
Papers: 45.0W
Citations: 704
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