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Surface segmentation for polycube construction based on generalized centroidal Voronoi tessellation

机译:基于广义质心Voronoi细分的多立方体构造的表面分割

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Centroidal Voronoi tessellation (CVT) has been employed to construct polycubes using the normal space of the input surface. In this paper, we develop a new two-step surface segmentation scheme for polycube construction using generalized CVT (gCVT). In the first step, eigenfunctions of the secondary Laplace operator (SLO) are coupled with the harmonic boundary-enhanced CVT (HBECVT) model to classify vertices of the surface into several components based on concave creases and convex ridges of an object. Neighbouring vertex information is incorporated into the clustering energy function to avoid over-segmentation, jaggy boundaries and noise effect. For each segmented component, in the second step we apply the skeleton information to define local coordinates and include them into the HBECVT model to further segment it into several patches, which are revised using predefined geometric constraints for valid polycube construction. Our skeleton-based CVT algorithm is suitable for slim cylindrical objects and can reduce unnecessary singularities with compact polycube structures. Based on the constructed polycube, we generate quality all-hexahedral meshes and volumetric T-meshes via parametric mapping. Several examples are presented in this paper to show the robustness of our scheme. (C) 2016 Elsevier B.V. All rights reserved.
机译:质心Voronoi镶嵌(CVT)已用于使用输入表面的法向空间构造多立方体。在本文中,我们为使用通用CVT(gCVT)的多立方体构造开发了一种新的两步曲面分割方案。第一步,将次级拉普拉斯算子(SLO)的本征函数与谐波边界增强CVT(HBECVT)模型耦合,以基于对象的凹折痕和凸脊将表面的顶点分类为几个分量。邻近的顶点信息被合并到聚类能量函数中,以避免过度分割,锯齿状边界和噪声影响。对于每个分割的组件,在第二步中,我们应用骨架信息来定义局部坐标,并将其包含在HBECVT模型中,以将其进一步分割为几个小块,并使用预定义的几何约束对其进行修改以构造有效的多维数据集。我们基于骨骼的CVT算法适用于细长的圆柱形物体,并可以通过紧凑的多立方体结构减少不必要的奇点。基于构造的多维数据集,我们通过参数映射生成高质量的全六面体网格和体积T型网格。本文提供了几个示例,以说明我们的方案的鲁棒性。 (C)2016 Elsevier B.V.保留所有权利。

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