CRI: CI-New: A Community Benchmarking Infrastructure for Birectional Reflectance Distribution Functions

该项目将支持开发一个测试平台应用程序套件，用于评估材料外观模型，这些模型描述了计算机图形研究中光线如何从表面反射。计算机图形学中的照片级真实感图像合成需要精确模拟光线通过虚拟场景的传输，从光源开始，从表面反射（基于材料模型），然后在相机处结束。因此，材料模型是计算机图形系统中的基本组成部分。 试验台将由三个组成部分组成：（1）现有材料模型的参考实现，（2）被优化以最佳地模仿真实的材料的外观的材料模型参数库，以及用于计算新的参数组以模仿新测量的材料的工具，以及（3）在线和离线分析工具，以帮助研究人员和从业者选择合适的模型，并帮助开发更准确的材料模型。 该测试平台的一个关键特性是，当人们提交新的材料模型实现，或模仿真实的材料的新策略，或评估模型准确性的新工具时，测试平台将自动对它们进行评估，并与测试平台中的所有模型和数据进行比较。这一关键特征至关重要，因为目前还没有一种好的方法让研究人员将他们的工作与其他人进行详尽的比较，这会减缓研究和图形应用的进展;试验平台将使新旧思想的比较变得更加容易，也使人们更容易理解哪些模型在哪些实际情况下最有效，使得外观建模对于计算机图形学内外的研究人员和从业者来说更加便携和可访问。 该试验台将推进计算机图形学相关领域的研究，并通过支持虚拟现实应用、产品预可视化、电子商务、安全和培训模拟器等方面的逼真度和视觉逼真度的提高，直接造福社会。存储库将由首席研究员填充双向反射分布函数（BRDF）、BRDF拟合策略和质量评估指标的初始参考实现集。 然后，研究界将能够向知识库贡献每个组件的新进展。此外，模拟所有BRDF模型物理材料反射行为的拟合BRDF参数（使用代码存储库中可用的每种不同BRDF拟合策略计算）将在存储库上以及通过网络公开提供。界面。当存储库中记录了新的算法或改进时，这些拟合的BRDF参数将动态更新。 网络界面将允许专家和从业者探索拟合的BRDF参数、相应的可视化和质量评估，以推动他们的研究或产品开发。该奖项反映了NSF的法定使命，并被认为值得通过使用基金会的知识价值和更广泛的影响审查标准进行评估来支持。

This project will support the development of a testbed application suite for evaluating material appearance models that describe how light is reflected from surfaces in computer graphics research. Photorealistic image synthesis in computer graphics requires accurate simulation of light transport through a virtual scene starting from the light sources, reflecting off surfaces (based on the material models), before ending at the camera. Hence, material models are a fundamental component in computer graphics systems. The testbed will consist of three integral components: (1) reference implementations of existing material models, (2) a library of material model parameters optimized to best mimic the appearance of real materials, as well as tools to compute new sets of parameters to mimic newly measured materials, and (3) online and offline analysis tools to aid researchers and practitioners to select appropriate models and to aid in the development of more accurate material models. A key feature of the testbed is that when people submit new material model implementations, or new strategies for mimicking real materials, or new tools for assessing the accuracy of models, the testbed will automatically evaluate them against all models and data in the testbed. This key feature is critical as there currently does not exist a good way for researchers to exhaustively 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 practical situations, making appearance modeling more portable and accessible to researchers and practitioners in and outside computer graphics. This testbed will advance research in areas related to computer graphics, as well as directly benefit society through supporting improved fidelity and visual realism in virtual reality applications, product pre-visualization, e-commerce, safety and training simulators, etc.The testbed will be in the form of a repository and a web interface. The repository will be populated by the lead investigator with an initial set of reference implementations of bidirectional reflectance distribution functions (BRDFs), BRDF fitting strategies, and quality assessment metrics. The research community will then be able to contribute new advances to each of these components to the repository. In addition, fitted BRDF parameters that mimic the reflectance behavior of physical materials for all BRDF models, computed with each of the different BRDF fitting strategies available in the code repository will be made publicly available, both on the repository as well as through the web interface. These fitted BRDF parameters will be dynamically updated when new algorithms or improvements are recorded in the repository. The web interface will allow experts and practitioners to explore the fitted BRDF parameters, corresponding visualization, and quality assessments to drive their research or product development.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.