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3D Mesh Segmentation Using Mean-Shifted Curvature

机译:使用平均移位曲率的3D网状分割

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摘要

An approach to segmentation of a 3D mesh is proposed. It employs mean-shift curvature to cluster vertices of the mesh. A region-growing scheme is then established for collecting them into connected subgraphs. The mesh faces consisting of vertices in the same subgraph constitute a patch while faces whose vertices are in different subgraphs are split and then lined out to near patches to complete the segmentation. To produce pleasing results, several ingredients are introduced into the segmentation pipeline. Firstly, we enhance the original model before mean-shifting and then transfer the curvature of the enhanced mesh to the original one in order to make the features distinguishable. To rectify the segmentation boundaries, the min-cut algorithm is used to repartition regions around boundaries. We also detect sharp features.
机译:提出了一种对3D网格进行分割的方法。它采用平均转换曲率到网格的集群顶点。然后建立一个生长的方案,用于将它们收集到连接的子图中。由同一子图中的顶点组成的网格面构成一个贴片,而顶点在不同子图中的面部被分割,然后在接近贴片上排出以完成分割。为了产生令人愉悦的结果,将几种成分引入分割管道。首先,我们在平均换档之前增强原始模型,然后将增强网格的曲率传送到原始的模型,以使特征可区分。为了纠正分割边界,最小剪切算法用于重置边界周围的区域。我们还检测到尖锐的功能。

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