IIS (G&V) EAGER: Modeling and Rendering a Fibre Bundle

摘要 计算机图形学领域的大量工作已经投入到火焰的真实建模和渲染中。建模和渲染底层木材燃烧过程最近受到了一些关注，但之前的工作并未考虑内部木材特性的影响，例如密度变化（即“颗粒”）和预燃烧过程（例如干燥）。一个称为“纤维束”的概念提出可以真实地代表木材等纤维材料的结构。纤维束由任意数量的几乎平行、不相交的曲线组成。空间中任意点的模型属性取决于 (a) 最接近该点的曲线和 (b) 到该曲线的距离。空间由这些曲线的 Voronoi 体积划分。这是图形建模中的一个新概念，如果可行，将在天然和合成纤维材料的表示方面带来变革，从而实现物理上正确的模拟。在计算这些纤维束时出现了重大问题，这项研究旨在表明可以以在时间和空间效率方面计算可行的方式开发和实施用于处理纤维束的数学算法。如果成功，该研究可以改进纤维材料的新表示。这不仅适用于木材燃烧，还适用于植物、植物材料或合成纤维建模的任何地方。影响超出了娱乐业。例如，它将为消防工程以及灾害规划和管理的设计系统提供必要的预测能力。

AbstractConsiderable work in computer graphics has gone into the realistic modeling and rendering of flames. Modeling and rendering the underlying wood combustion process has received some attention recently, but prior work has not incorporated effects of internal wood properties such as density variation (i.e. ?grain?) and pre-combustion processes such as drying. A concept called ?fiber bundles? is proposed that can realistically represent the structure of fibrous materials such as wood. Fiber bundles consist of an arbitrarily large number of almost-parallel, never-intersecting curves. Model properties at any point in space depend on (a) the curve that comes closest to that point and (b) the distance to that curve. Space is partitioned by the Voronoi volume of these curves. This is a new concept in graphical modeling and, if viable, would be transformative in the representation of both natural and synthetic fibrous materials, allowing for physically correct simulation. Significant issues arise in computing these fiber bundles and this research is designed to show that mathematical algorithms for processing fiber bundles can be developed and implemented in ways that are computationally viable in terms of both time and space efficiency.If successful, the research can lead to improved new representation of fibrous materials. This will be applicable not only for wood combustion, but also wherever plants, plant materials, or synthetic fibers are modeled. The impact goes beyond the entertainment industry. It would, for example, provide essential predictive capabilities to design systems for fire engineering as well as for disaster planning and management.