SEG-MAT: 3D Shape Segmentation Using Medial Axis Transform
SEG-MAT: 3D Shape Segmentation Using Medial Axis Transform
复制标题
SEG-MAT：使用中轴变换进行 3D 形状分割
DOI：
10.1109/tvcg.2020.3032566
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发表时间：
2022-06-01
影响因子：
5.2
通讯作者：
Wang, Wenping
中科院分区：
文献类型：
--
作者：
Lin, Cheng;Liu, Lingjie;Wang, Wenping
将任意3D对象分割成结构上有意义的组成部分是在广泛的计算机图形应用中遇到的一个基本问题。现有的三维形状分割方法由于缺乏全局考虑，利用低层特征进行几何处理复杂，计算量大，分割结果碎片化。我们提出了一种基于输入形状中轴变换的有效方法，称为SEG-MAT。具体地说，利用编码在MAT中的丰富的几何和结构信息，我们能够开发一种简单而有原则的方法来有效地识别3D形状不同部分之间的各种类型的连接。大量的评估和比较表明，我们的方法在分割质量方面优于最先进的方法，而且速度也快了一个数量级。
Segmenting arbitrary 3D objects into constituent parts that are structurally meaningful is a fundamental problem encountered in a wide range of computer graphics applications. Existing methods for 3D shape segmentation suffer from complex geometry processing and heavy computation caused by using low-level features and fragmented segmentation results due to the lack of global consideration. We present an efficient method, calledSEG-MAT, based on the medial axis transform (MAT) of the input shape. Specifically, with the rich geometrical and structural information encoded in the MAT, we are able to develop a simple and principled approach to effectively identify the various types of junctions between different parts of a 3D shape. Extensive evaluations and comparisons show that our method outperforms the state-of-the-art methods in terms of segmentation quality and is also one order of magnitude faster.