Simulating volumetric participating media visual effects with Monte Carlo methods

使用蒙特卡罗方法模拟体积参与媒体视觉效果

• 批准号: 543410-2019
• 负责人: Nowrouzezahrai, Derek
• 金额: $ 1.07万
• 依托单位: McGill University
• 依托单位国家: 加拿大
• 项目类别: Collaborative Research and Development Grants
• 财政年份: 2021
• 资助国家: 加拿大
• 起止时间: 2021-01-01 至 2022-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=720705
• 关键词: Simulating; volumetric; participating; media; visual

The realistic simulation of lighting in realistic environments has applications broadly spanning many industries: architectural visualization, product design, medical imaging, visual effects for feature films, video games, virtual reality and augmented reality. In these contexts, faithfully simulating the physical behaviour of light in volumetric participating media, like clouds or particulate fluids, is essential in order to generate realistic images and/or image sequences. Monte Carlo-based techniques rely on statistical methods to synthesize this behaviour, by simulating the scattering of many billions-to-trillions of (virtual) photons in a (virtual) environment in order to generate a single image. As such, incorporating the effects of volumetric media remains a costly computation and a continuing area of focus in the fields of realistic image synthesis and radiative transfer over the last five decades.This collaborative project will address this problem by developing novel Monte Carlo-based solutions. Specifically, these solutions will adapt and apply concepts from the computational statistics literature, leveraging the vast amount of work on variance reduction and correlated sampling, two mathematical tools that have proven successful in the context of similar problems outside of image synthesis. Our work will be incorporated into an industrial-caliber software platform, Autodesk's Arnold Rendering Engine, which will allow us to benchmark the efficacy of the techniques we develop against the state-of-the-art of existing high-end software solutions. Moreover, we will leverage and build atop of Autodesk's existing expertise in these areas, working hand-in-hand with their rendering engineers and digital content creators in order to build a larger set of testing scenarios in order to stress-test the solutions we develop. One side-effect of such rigorous testing is that we will develop more consistent and representative benchmarks for the community to base future developments on. The techniques we develop will have immediate impact on the workflows and content generation capabilities of Autodesk's product suite, starting most immediately with their Arnold Rendering Engine.

现实环境中的照明的逼真模拟具有广泛的应用，跨越许多行业：建筑可视化，产品设计，医学成像，故事片的视觉效果，视频游戏，虚拟现实和增强现实。在这些背景下，为了生成逼真的图像和/或图像序列，忠实地模拟光在体积参与介质（如云或颗粒流体）中的物理行为是必不可少的。基于蒙特卡洛的技术依赖于统计方法来合成这种行为，通过模拟数十亿至数万亿（虚拟）光子在（虚拟）环境中的散射来生成单个图像。因此，将体积介质的影响仍然是一个昂贵的计算，并在现实的图像合成和辐射传输在过去的50年的持续关注领域。这个合作项目将通过开发新的蒙特卡洛为基础的解决方案来解决这个问题。具体来说，这些解决方案将适应和应用计算统计文献中的概念，利用方差缩减和相关采样方面的大量工作，这两种数学工具在图像合成之外的类似问题中已经证明是成功的。我们的工作将被纳入一个工业级的软件平台，Autodesk的Arnold渲染引擎，这将使我们能够对我们开发的技术与现有高端软件解决方案的最先进水平进行基准测试。此外，我们将利用Autodesk在这些领域的现有专业知识，与他们的渲染工程师和数字内容创作者携手合作，以构建更大的测试场景，从而对我们开发的解决方案进行压力测试。这种严格测试的一个副作用是，我们将为社区开发更一致和更有代表性的基准，以作为未来开发的基础。我们开发的技术将对Autodesk产品套件的工作流程和内容生成功能产生直接影响，最直接的是从他们的Arnold渲染引擎开始。