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1D sweep-and-prune self-collision detection for deforming cables

机译:一维扫描和修剪自碰撞检测变形电缆

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Detecting self-collision for cables and similar objects is an important part of numerous models in computational biology (protein chains), robotics (electric cables), hair modeling, computer graphics, etc. In this paper the 1D sweep-and-prune algorithm for detecting self-collisions of a deforming cable comprising linear segments is investigated. The sweep-and-prune algorithm is compared with other state-of-the-art self-collision detection algorithms for deforming cables and is shown to be up to an order of magnitude faster than existing algorithms for cables with a high proportion of segments moving. We also present a multithreaded version of the algorithm and investigate its performance. In addition, we present worst-case bounds for 1D sweep-and-prune algorithms whereby the colliding objects do not exceed a certain object density, and apply these results to deforming cables.
机译:检测电缆和类似物体的自碰撞是计算生物学(蛋白质链),机器人技术(电缆),头发建模,计算机图形学等众多模型的重要组成部分。本文采用一维扫掠和修剪算法研究了检测包括线性段的变形电缆的自碰撞。将扫描和修剪算法与其他用于变形电缆的最新自碰撞检测算法进行了比较,结果表明,该算法比现有的用于分段移动比例较高的电缆的算法要快一个数量级。 。我们还提出了该算法的多线程版本,并研究了其性能。此外,我们为一维扫掠和修剪算法提供了最坏情况的边界,其中碰撞对象不超过特定对象密度,并将这些结果应用于变形电缆。

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