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L_1-Medial Skeleton of Point Cloud

机译:L_1-点云的内侧骨架

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摘要

We introduce L_1-medial skeleton as a curve skeleton representation for 3D point cloud data. The L_1-median is well-known as a robust global center of an arbitrary set of points. We make the key observation that adapting L_1-medians locally to a point set representing a 3D shape gives rise to a one-dimensional structure, which can be seen as a localized center of the shape. The primary advantage of our approach is that it does not place strong requirements on the quality of the input point cloud nor on the geometry or topology of the captured shape. We develop a L_1-medial skeleton construction algorithm, which can be directly applied to an unoriented raw point scan with significant noise, outliers, and large areas of missing data. We demonstrate L_1-medial skeletons extracted from raw scans of a variety of shapes, including those modeling high-genus 3D objects, plant-like structures, and curve networks.
机译:我们引入L_1中间骨架作为3D点云数据的曲线骨架表示。 L_1中值众所周知是任意点集的鲁棒全局中心。我们的主要观察结果是,使L_1中位数局部适应表示3D形状的点集会产生一维结构,该结构可以看作是形状的局部中心。我们方法的主要优点是,它对输入点云的质量和捕获形状的几何形状或拓扑结构都没有严格的要求。我们开发了一种L_1-内侧骨架构造算法,该算法可以直接应用于具有明显噪声,离群值和大面积缺失数据的无方向性原始点扫描。我们演示了从各种形状的原始扫描中提取的L_1中间骨骼,包括那些对高属3D对象,类植物结构和曲线网络进行建模的模型。

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