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

摘要计算机图形学中值得考虑的工作已经进入了火焰的逼真建模和渲染。木材燃烧过程的建模和渲染最近受到了一些关注，但以前的工作没有考虑木材内部性质的影响，如密度变化(即纹理？)以及燃烧前的干燥等过程。一种叫做纤维束的概念？提出了一种能够逼真地表示木材等纤维材料结构的方法。纤维束由任意数量的几乎平行、永不相交的曲线组成。空间中任何点的模型特性取决于(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具有变革性，允许进行物理上正确的模拟。在计算这些纤维束时出现了重要的问题，本研究旨在表明，处理纤维束的数学算法可以以在时间和空间效率方面在计算上可行的方式来开发和实现。如果成功，该研究可以导致改进纤维材料的新表示。这不仅适用于木材燃烧，也适用于任何模拟植物、植物材料或合成纤维的地方。其影响不仅限于娱乐业。例如，它将为消防工程以及灾害规划和管理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.