骨架生长:一种基于矢量场的三维曲线骨架提取算法

N. Pantuwong, Masanori Sugimoto
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引用次数: 11

摘要

矢量场法是三维曲线骨架提取算法之一。通常,将三维物体内部矢量场中的关键点连接起来形成曲线骨架。然而,临界点通常不会分布到3D物体的所有重要部分。因此,使用其他特征来产生可靠的结果。尽管这种策略可以提供捕获所有重要部分的曲线骨架,但曲线骨架通常带有不必要的部分。本文提出了一种自动生成少量曲线骨架的骨架生长算法。它搜索一组高曲率边界体素作为起点,以找到一组合适的种子点,这些种子点将用于生长曲线骨架。我们提出了一种可以降低骨架噪声密度的不必要的片段去除算法。为了避免在不相关的方向上进行搜索,提出了一种方向选择算法。所提出的方法可以产生一个单一的可靠的结果曲线骨架,可以应用于许多不同的应用,包括匹配、动画和可视化。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Skeleton-growing: a vector-field-based 3D curve-skeleton extraction algorithm
The vector-field-based method is one of the 3D curve-skeleton extraction algorithms. Typically, critical points in the vector field inside 3D objects are connected to form the curve-skeleton. However, critical points usually do not distribute to all important parts of the 3D object. Therefore, other features are used to produce a reliable result. Although this strategy can deliver a curve-skeleton that captures all of the important parts, the curve-skeleton usually comes with unnecessary segments. This paper proposes the skeleton-growing algorithm that automatically produces the curve-skeleton with small amounts of such segments. It searches for a set of high-curvature boundary voxels as starting points to find a set of suitable seed points that will be used to grow the curve-skeleton. We propose an unnecessary segment removal algorithm that can reduce the skeleton-noise density. A direction-selection algorithm is developed to avoid searching in irrelevant directions. The proposed method can produce a single reliable result curve-skeleton that could be applied in many different applications, including matching, animation, and visualization.
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