We introduce a novel approach for the reconstruction of tubular shapes from skeletal representations. Our method processes all skeletal points as a whole, eliminating the need for splitting input structure into multiple segments. We represent the tubular shape as a truncated signed distance function (TSDF) in a voxel hashing manner, in which the signed distance between a voxel center and the object is computed through a simple geometric algorithm. Our method does not involve any surface sampling scheme or solving large matrix equations, and therefore is a faster and more elegant solution for tubular shape reconstruction compared to other approaches. Experiments demonstrate the efficiency and effectiveness of the proposed method. Code is avaliable at https://github.com/wlsdzyzl/Dragon.

翻译：我们提出了一种从骨架表示重建管状形态的新方法。本方法将所有骨架点作为一个整体进行处理，无需将输入结构分割成多个片段。我们采用体素哈希方式将管状形态表示为截断符号距离函数（TSDF），其中体素中心与对象之间的符号距离通过简单的几何算法计算得出。该方法无需进行任何表面采样或求解大型矩阵方程，因此相比其他管状形态重建方法更为快速且优雅。实验证明了该方法的效率与有效性。代码可在 https://github.com/wlsdzyzl/Dragon 获取。