Adaptive Multi-level Multi-phenomena Appearance Models

自适应多级多现象外观模型

• 批准号: RGPIN-2015-04378
• 负责人: Poulin, Pierre
• 金额: $ 2.62万
• 依托单位: Université de Montréal
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2016
• 资助国家: 加拿大
• 起止时间: 2016-01-01 至 2017-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=612928
• 关键词: Adaptive; Multi; level; phenomena; Appearance

Rendering realistic synthetic scenes requires an accurate representation of 3D objects and light transport. The result of this simulation is filtered in an image as surface appearance, which varies with distance, orientation, incident illumination, reflection properties, interreflections, subsurface scattering, microgeometry, and textures. Light transport and visibility are often resolved using a combination of Monte Carlo (MC) sampling and ray tracing, well adapted through multiple sampling to most integration problems in rendering. However, they are inefficient in complex scenes because they operate on the finest-scale of the scene representation, and thus, this approach does not scale for real-time rendering of complex scenes nor offline high-quality rendering. Instead, we propose to adapt pre-filtered representations of geometries, visibility, and appearances to the pixel size, i.e., to find an appropriate level-of-detail computation for light-object interactions. Our recent LEADR method computes the color over an entire pixel footprint, interactively and independent of the footprint's size. It is filterable, efficient, suitable for GPUs, scalable with complexity, and high-quality, but it is limited to textured height maps under direct illumination. This research program will design several novel hierarchical representations of surfaces, volumes, visibility/transparency, textures, and light transport, to cast the phenomena that affect appearance into our prefiltered approach. We propose to generalize the concept of light transport within a black box to all combined factors affecting appearance, thus efficiently determining the appropriate representation under viewing and illumination conditions, leading to real-time rendering of complex scenes, as well as an adapted scheme to be integrated in path-tracing methods. We will build knowledge from a number of specific case studies, such as grass-to-lawn, tree-to-canopy, sand-to-dune, fabrics-to-drapes, building-to-city, etc. We will develop interpolation schemes between two adjacent levels in a hierarchy. Then we will work our way up by introducing representations at coarser hierarchy levels, and adapting interpolation schemes. Next we will add the other effects affecting appearance, integrating them into a more general model. Our long-term goal is to develop a unified multi-level multi-phenomena appearance scheme suitable for high-quality real-time and offline rendering.

渲染逼真的合成场景需要准确地表示3D对象和光线传输。模拟的结果在图像中作为表面外观进行过滤，表面外观随距离、方向、入射照明、反射属性、互反射、次表面散射、微观几何和纹理而变化。光线传输和可见性通常使用蒙特卡罗(MC)采样和光线跟踪的组合来解决，通过多次采样很好地适应了渲染中的大多数集成问题。然而，它们在复杂场景中的效率很低，因为它们在场景表示的最精细尺度上操作，因此，该方法不适用于复杂场景的实时渲染或离线高质量渲染。相反，我们建议根据像素大小调整几何、可见性和外观的预过滤表示，即为光-对象交互找到合适的细节级别计算。我们最近的Leadr方法在整个像素足迹上计算颜色，并且是交互的，与足迹的大小无关。它可过滤，效率高，适用于GPU，可随复杂性扩展，质量高，但仅限于直接照明下的纹理高度贴图。 这项研究计划将设计几种新颖的表面、体积、可见性/透明度、纹理、颜色和光线传输的层次结构表示法，将影响外观的现象投射到我们的预过滤方法中。我们建议将黑盒内的光传输的概念推广到所有影响外观的组合因素，从而有效地确定在观看和照明条件下的适当表示，从而导致复杂场景的实时渲染，以及一种适应的方案，以集成到路径跟踪方法中。 我们将从一些具体的案例研究中建立知识，例如从草地到草坪，从树木到树冠，从沙子到沙丘，从织物到窗帘，从建筑到城市等。我们将在层次结构中相邻的两个级别之间开发内插方案。然后，我们将通过在更粗的层次级别引入表示法并调整插补方案来逐步提升。接下来，我们将添加影响外观的其他效果，将它们整合到更一般的模型中。我们的长期目标是开发一个统一的多层次、多现象的外观方案，适合高质量的实时和离线渲染。