论文标题
通过本地分离器的骨骼化
Skeletonization via Local Separators
论文作者
论文摘要
我们提出了一种用于曲线骨架计算的新算法，该算法与以前的算法不同，它通过基于局部分离器的概念而不同。这种方法的主要好处是，它能够捕获相对细节，并且在一系列形状表示方面可以稳健地工作。具体而言，我们的方法在形状表示方面起作用，可以将其解释为空间嵌入式图。这样的表示包括网格，体积形状和从点云计算的图。我们描述了一个简单的管道，其中最初将几何数据转换为图形，可选地简化，局部分离器被计算和选择，最后构建了一个骨架。我们测试有关多边形网格，体积形状和点云的管道。最后，我们将结果与其他根据性能和质量进行骨骼化的方法进行比较。
We propose a new algorithm for curve skeleton computation which differs from previous algorithms by being based on the notion of local separators. The main benefits of this approach are that it is able to capture relatively fine details and that it works robustly on a range of shape representations. Specifically, our method works on shape representations that can be construed as a spatially embedded graphs. Such representations include meshes, volumetric shapes, and graphs computed from point clouds. We describe a simple pipeline where geometric data is initially converted to a graph, optionally simplified, local separators are computed and selected, and finally a skeleton is constructed. We test our pipeline on polygonal meshes, volumetric shapes, and point clouds. Finally, we compare our results to other methods for skeletonization according to performance and quality.
