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Partwise Cross-Parameterization via Nonregular Convex Hull Domains

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5 Author(s)
Huai-Yu Wu ; Key Lab. of Machine Perception (MOE), Peking Univ., Beijing, China ; Chunhong Pan ; Hongbin Zha ; Qing Yang
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In this paper, we propose a novel partwise framework for cross-parameterization between 3D mesh models. Unlike most existing methods that use regular parameterization domains, our framework uses nonregular approximation domains to build the cross-parameterization. Once the nonregular approximation domains are constructed for 3D models, different (and complex) input shapes are transformed into similar (and simple) shapes, thus facilitating the cross-parameterization process. Specifically, a novel nonregular domain, the convex hull, is adopted to build shape correspondence. We first construct convex hulls for each part of the segmented model, and then adopt our convex-hull cross-parameterization method to generate compatible meshes. Our method exploits properties of the convex hull, e.g., good approximation ability and linear convex representation for interior vertices. After building an initial cross-parameterization via convex-hull domains, we use compatible remeshing algorithms to achieve an accurate approximation of the target geometry and to ensure a complete surface matching. Experimental results show that the compatible meshes constructed are well suited for shape blending and other geometric applications.

Published in:

Visualization and Computer Graphics, IEEE Transactions on  (Volume:17 ,  Issue: 10 )

Date of Publication:

Oct. 2011

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