Medial axis extraction and shape manipulation of solid objects using parabolic PDEs

Haixia Du, Hong Qin
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引用次数: 34

Abstract

Shape skeletonization (i.e., medial axis extraction) is powerful in many visual computing applications, such as pattern recognition, object segmentation, registration, and animation. This is because medial axis (or skeleton) provides more compact representations for solid models while preserving their topological properties and other features. Meanwhile, PDE techniques are widely utilized in computer graphics fields to model solid objects and natural phenomena, formulate physical laws to govern the behavior of objects in real world, and provide means to measure the feature of movements, such as velocity, acceleration, change of energy, etc. Certain PDEs such as diffusion equations and Hamilton-Jacobi equation have been used to detect medial axes of 2D images and volumetric data with ease. However, using such equations to extract medial axes or skeletons for solid objects bounded by arbitrary polygonal meshes directly is yet to be fully explored. In this paper, we expand the use of diffusion equations to approximate medial axes of arbitrary 3D solids represented by polygonal meshes based on their differential properties. It offers an alternative but natural way for medial axis extraction for commonly used 3D polygonal models. By solving the PDE along time axis, our system can not only quickly extract diffusion-based medial axes of input meshes, but also allow users to visualize the extraction process at each time step. In addition, our model provides users a set of manipulation toolkits to sculpt extracted medial axes, then use diffusion-based techniques to recover corresponding deformed shapes according to the original input datasets. This skeleton-based shape manipulation offers a fast and easy way for animation and deformation of complicated solid objects.
使用抛物型偏微分方程的实体内轴线提取和形状处理
形状骨架化(即中轴提取)在许多视觉计算应用中都很强大,例如模式识别、对象分割、配准和动画。这是因为中轴(或骨架)为实体模型提供了更紧凑的表示,同时保留了它们的拓扑属性和其他特征。同时,PDE技术被广泛应用于计算机图形学领域,用于对实体物体和自然现象进行建模,制定控制现实世界中物体行为的物理规律,并为测量运动特征(如速度、加速度、能量变化等)提供手段。某些偏微分方程(如扩散方程和Hamilton-Jacobi方程)已被用于方便地检测二维图像和体积数据的中轴线。然而,如何利用这些方程直接提取以任意多边形网格为界的实体的内轴线或骨架,目前还没有得到充分的探索。在本文中,我们将扩散方程的应用扩展到近似多边形网格表示的任意三维实体的中间轴。它为常用的三维多边形模型的中轴提取提供了一种自然的替代方法。通过求解沿时间轴的偏微分方程,我们的系统不仅可以快速提取基于扩散的输入网格的中间轴,而且可以让用户可视化每个时间步的提取过程。此外,我们的模型为用户提供了一套操作工具包来雕刻提取的内侧轴,然后使用基于扩散的技术根据原始输入数据集恢复相应的变形形状。这种基于骨架的形状操作为复杂实体的动画和变形提供了一种快速简便的方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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