CI-P: Planning a Community Benchmarking Infrastructure for Bidirectional Reflectance Distribution Functions

CI-P：规划双向反射率分布函数的社区基准基础设施

• 批准号: 1625879
• 负责人: Pieter Peers
• 金额: $ 10万
• 依托单位: College of William and Mary
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-08-01 至 2018-01-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1625879&HistoricalAwards=false
• 关键词: CI; Planning; Community; Benchmarking; Infrastructure

This project will support the planning and building of an initial testbed application for evaluating material models that describe how light is reflected from surfaces in computer graphics research. After talking with interested researchers in the community, the lead investigator will build an application that allows anyone to submit and download three important types of data for doing this research: (1) reference implementations of material models, (2) measures of how well the predicted light reflections of a model match real examples, and (3) examples of measured reflections from physical materials to compare against. When people submit new material model implementations, the application will automatically run all of the models it contains using all of the measures and measured examples available. This is an important advance because currently there is no good way for researchers to compare their work against others', which slows down progress in both research and graphics applications; the testbed will make it much easier to compare new ideas to old ones, as well as to understand which models work best in which situations. This will advance research in a number of areas related to computer graphics, as well as directly benefiting society through improving graphics in real applications including virtual reality, animation, and data visualization. To do this, the lead investigator will create a repository with an initial set of reference algorithms, datasets, fitting functions, and evaluation metrics based on existing research around bidirectional reflectance distribution functions (BRDFs). Other researchers will be able to contribute to the repository through an Application Programming Interface (API) that allows for easy addition of new items; it will then dynamically report on run all-against-all comparisons with existing items in the repository. During this planning grant the lead investigator will develop the initial infrastructure both to demonstrate a proof-of-concept and to present a concrete artifact that can jump start the discussion of how to make the repository more useful to the broader research community. Although starting with researchers most directly involved with BRDFs, the community will eventually include people from a number of related research areas, including non-linear optimization, human perception, rendering, photorealistic visualization, and computer vision.

该项目将支持计划和构建初始测试床应用程序，以评估材料模型，这些模型描述了计算机图形研究中如何从表面反射的光线。 在与社区中有兴趣的研究人员进行了交谈之后，首席研究人员将构建一个应用程序，该应用程序可以提交和下载进行此研究的三种重要数据类型：（1）材料模型的参考实现，（2）衡量模型的预测光反射如何匹配真实示例的预测光线以及（3）来自物理材料的测量材料的示例。 当人们提交新的材料模型实施时，该应用程序将使用所有可用的措施和可用示例自动运行其包含的所有模型。 这是一个重要的进步，因为目前，研究人员没有很好的方法将其工作与他人进行比较，这减慢了研究和图形应用的进展。测试台将使将新想法与旧想法进行比较，并了解哪些模型在哪种情况下最有效。 这将推进与计算机图形相关的许多领域的研究，并通过改善包括虚拟现实，动画和数据可视化在内的真实应用中的图形来直接使社会受益。为此，主要研究人员将基于关于双向反射分布函数（BRDFS）的现有研究的初始参考算法，数据集，拟合功能和评估指标创建一个存储库。 其他研究人员将能够通过应用程序编程接口（API）为存储库做出贡献，该界面允许添加新项目；然后，它将与存储库中现有项目进行全面比较，以动态报告。 在这项计划赠款中，首席调查员将开发最初的基础设施，以证明概念证明并提出一个具体的工件，可以开始讨论如何使存储库对更广泛的研究社区更有用。 尽管从最直接与BRDF相关的研究人员开始，但社区最终将包括来自许多相关研究领域的人，包括非线性优化，人类感知，渲染，逼真的可视化和计算机视觉。