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Mollifying Realistic Image Synthesis for Time Constrained Rendering

缓解时间受限渲染的真实图像合成

基本信息

批准号：
323377784
负责人：
Professor Dr.-Ing. Carsten Dachsbacher
金额：
--
依托单位：
Lehrstuhl für Computergrafik
依托单位国家：
德国
项目类别：
Research Grants
财政年份：
2016
资助国家：
德国
起止时间：
2015-12-31 至 2020-12-31
项目状态：
已结题

来源：
https://gepris.dfg.de/gepris/projekt/323377784?language=en
关键词：
Mollifying Realistic Image Synthesis Time

项目摘要

Realistic image synthesis, or rendering, is a key problem in computer graphics with numerous application areas, from digital entertainment to architecture and industrial design. The goal of most previous rendering algorithms is to converge to the ground truth solution as quickly as possible with increasing computation time. Computation typically continues until desired quality criteria are met, but the desired computation time is not an input to the renderer. In contrast to this, in this project we consider the problem to obtain the best possible approximate solution under a given time constraint. A key idea is to achieve this by modifying the rendering problem at hand, that is the scene and the light transport simulation including image reconstruction, to obtain easier problems. This is often called "mollification". Mollification allows us to achieve better approximations of the desired image within a given time budget. Solving the mollified problem may in general not converge to the ground truth, but it will provide a better approximation given a limited time compared to solving the original problem. We believe this problem statement is highly relevant in application scenarios where the user cannot be expected to simply wait for an arbitrary amount of time until a simulation provides acceptable results. For example during interactive modeling or design, it is much more useful for users to specify a given amount of time they are willing to wait. Our proposed techniques attempt to deliver the best possible approximate solution in this time frame. In this project we will develop a theoretical framework for mollification, and practical algorithms to demonstrate its benefits.

真实感图像合成或渲染是计算机图形学中的一个关键问题，具有许多应用领域，从数字娱乐到建筑和工业设计。大多数以前的渲染算法的目标是随着计算时间的增加尽可能快地收敛到地面实况解决方案。计算通常继续，直到满足期望的质量标准，但是期望的计算时间不是渲染器的输入。与此相反，在这个项目中，我们考虑在给定的时间约束下获得最佳的近似解的问题。一个关键的想法是通过修改手头的渲染问题来实现这一点，即场景和光传输模拟，包括图像重建，以获得更容易的问题。这通常被称为“缓和”。柔化使我们能够在给定的时间预算内实现更好的近似所需的图像。解决缓和的问题通常可能不会收敛到地面真理，但与解决原始问题相比，它将在有限的时间内提供更好的近似。我们相信这个问题的陈述是高度相关的应用场景中，用户不能被期望简单地等待任意量的时间，直到模拟提供可接受的结果。例如，在交互式建模或设计期间，用户指定他们愿意等待的给定时间量会更有用。我们提出的技术试图在这个时间范围内提供最佳的近似解决方案。在这个项目中，我们将开发一个理论框架，软化，和实际的算法，以证明其好处。