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.

中文翻译：

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通过局部分隔符的骨架化

我们提出了一种新的曲线骨架计算算法，该算法与以前的算法不同，它基于局部分隔符的概念。这种方法的主要好处是它能够捕获相对精细的细节，并且可以在一系列形状表示上稳健地工作。具体来说，我们的方法适用于可以解释为空间嵌入图的形状表示。此类表示包括网格、体积形状和从点云计算的图形。我们描述了一个简单的管道，其中几何数据最初转换为图形，可选地简化，计算和选择局部分隔符，最后构建骨架。我们在多边形网格、体积形状和点云上测试我们的管道。最后，