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Sampled medial loci and boundary differential geometry

机译:采样的内侧基因座和边界微分几何

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We introduce a novel algorithm to compute a dense sample of points on the medial locus of a polyhedral object, with a guarantee that each medial point is within a specified tolerance ¿ from the medial surface. Motivated by Damon's work on the relationship between the differential geometry of the smooth boundary of an object and its medial surface, we then develop a computational method by which boundary differential geometry can be recovered directly from this dense medial point cloud. Experimental results on models of varying complexity demonstrate the validity of the approach, with principal curvature values that are consistent with those provided by an alternative method that works directly on the boundary. As such, we demonstrate the richness of a dense medial point cloud as a shape descriptor for 3D data processing.
机译:我们引入一种新颖的算法来计算多面体对象的内侧轨迹上的点的密集样本,并保证每个内侧点均在距内侧表面的指定公差γ范围内。达蒙(Damon)研究物体光滑边界的微分几何与其中间表面之间的关系后,我们开发了一种计算方法,利用该方法可以直接从密集的中间点云中恢复边界微分几何。在各种复杂性模型上的实验结果证明了该方法的有效性,其主曲率值与直接在边界上工作的另一种方法提供的主曲率值一致。这样,我们证明了密集的中间点云作为3D数据处理的形状描述符的丰富性。

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