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Manifold Parameterization

Authors: Lei Zhang 0021; Ligang Liu 0001; Zhongping Ji; Guojin Wang;

Manifold Parameterization

Abstract

Manifold parameterization considers the problem of parameterizing a given triangular mesh onto another mesh surface, which could be particularly plane or sphere surfaces. In this paper we propose a unified framework for manifold parameterization between arbitrary meshes with identical genus. Our approach does this task by directly mapping the connectivity of the source mesh onto the target mesh surface without any intermediate domain and partition of the meshes. The connectivity graph of source mesh is used to approximate the geometry of target mesh using least squares meshes. A subset of user specified vertices are constrained to have the geometry information of the target mesh. The geometry of the mesh vertices is reconstructed while approximating the known geometry of the subset by positioning each vertex approximately at the center of its immediate neighbors. This leads to a sparse linear system which can be effectively solved. Our approach is simple and fast with less user interactions. Many experimental results and applications are presented to show the applicability and flexibility of the approach.

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Powered by OpenAIRE graph
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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!
11
Average
Average
Top 10%
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