GAMES Webinar 2018 -78期(Siggraph Asia 2018论文报告)| 郭煜(美国加州大学尔湾分校),孙天成(加州大学圣地亚哥分校)

【GAMES Webinar 2018-78期(Siggraph Asia 2018论文报告)】
报告嘉宾1:郭煜,美国加州大学尔湾分校
报告时间:2018年12月20日 下午2:00-2:45(北京时间)
主持人:董悦,微软亚洲研究院(个人主页:http://yuedong.shading.me
报告题目:多层材质的渲染
报告摘要:
在真实世界中,物体的表面大多可以看作是层级材质:比如木制家具的表面,是在带纹理的木质原材料上涂一层半透明的油漆,油漆上面再打一层蜡;汽车外壳亦是如此,金属涂层给汽车带来更好的视觉质感;乃至于纺织品、人体组织等都可以用类似的分层材质来模拟。然而,传统的路径追踪(path tracing)方法很难实现高效的计算,因为光线会在层与层之间进行复杂的反射折射散射以及吸收。基于分层模型的最基本假设(也就是光线射入一个无限大的多层平面,经过一系列传递后离开,不考虑入射出射点的位置,只考虑入射出射方向),我们重新推导了辐射传递方程(radiative transfer equation),并用蒙特卡洛方法给出无偏的BSDF模型。最后我们给出了一些渲染例子来展示该方法的通用性,包括了非均质(heterogeneous)材料,各项异性(anisotropic)材料,以及带有法向的表面。
讲者简介:
郭煜,加州大学尔湾分校(UCI)三年级博士生,师从赵爽教授。曾在中科院深圳先进技术研究院和新加坡南洋理工大学进行学习和研究工作。研究领域为计算机图形学和计算机视觉,目前主要研究方向是真实感渲染。
讲者个人主页:https://www.ics.uci.edu/~yug10/

 

报告嘉宾2:孙天成,加州大学圣地亚哥分校
报告时间:2018年12月20日 下午2:45-3:00(北京时间)
主持人:董悦,微软亚洲研究院(个人主页:http://yuedong.shading.me
报告题目:Connecting Measured BRDFs to Analytic BRDFs by Data-Driven Diffuse-Specular Separation
报告摘要:
The bidirectional reflectance distribution function (BRDF) is crucial for modeling the appearance of real-world materials. In production rendering, analytic BRDF models are often used to approximate the surface appearance since they are compact and flexible. Measured BRDFs usually have a more realistic appearance, but consume much more storage and are hard to modify. In this paper, we propose a novel framework for connecting measured and analytic BRDFs. First, we develop a robust method for separating a measured BRDF into diffuse and specular components. This is commonly done in analytic models, but has been difficult previously to do explicitly for measured BRDFs. This diffuse-specular separation allows novel measured BRDF editing on the diffuse and specular parts separately. In addition, we conduct analysis on each part of the measured BRDF, and demonstrate a more intuitive and lower-dimensional PCA model than Nielsen et al. [2015]. In fact, our measured BRDF model has the same number of parameters (8 parameters) as the commonly used analytic models, such as the GGX model. Finally, we visualize the analytic and measured BRDFs in the same space, and directly demonstrate their similarities and differences. We also design an analytic fitting algorithm for two-lobe materials, which is more robust, efficient and simple, compared to previous non-convex optimization-based analytic fitting methods.
讲者简介:
Tiancheng Sun is a second-year PhD student in UC San Diego. His advisor is Ravi Ramamoorthi. Before UCSD, he was an undergraduate student in Yao Class, Tsinghua University. He had also done research in KAUST with Wolfgang Heidrich, in University of Zaragoza with Diego Gutierrez and Belen Masia, and in Google with Yun-Ta Tsai and Jon Barron. His main research interest lies in material modelling, acquisition, and reproduction. His most recent research interest is image-based rendering. His work on BRDF gamut mapping won the 1st place at the 2018 ACM Student Research Competition (undergraduate category).
讲者个人主页:http://www.kevinkingo.com

 

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