Stylization-based ray prioritization for guaranteed frame rates

Bernhard Kainz, M. Steinberger, Stefan Hauswiesner, Rostislav Khlebnikov, D. Schmalstieg
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引用次数: 3

Abstract

This paper presents a new method to control graceful scene degradation in complex ray-based rendering environments. It proposes to constrain the image sampling density with object features, which are known to support the comprehension of the three-dimensional shape. The presented method uses Non-Photorealistic Rendering (NPR) techniques to extract features such as silhouettes, suggestive contours, suggestive highlights, ridges and valleys. To map different feature types to sampling densities, we also present an evaluation of the features impact on the resulting image quality. To reconstruct the image from sparse sampling data, we use linear interpolation on an adaptively aligned fractal pattern. With this technique, we are able to present an algorithm that guarantees a desired minimal frame rate without much loss of image quality. Our scheduling algorithm maximizes the use of each given time slice by rendering features in order of their corresponding importance values until a time constraint is reached. We demonstrate how our method can be used to boost and guarantee the rendering time in complex ray-based environments consisting of geometric as well as volumetric data.
基于风格化的光线优先级保证帧率
本文提出了一种控制复杂光线渲染环境下优美场景退化的新方法。它提出用物体特征约束图像采样密度,已知这些特征支持对三维形状的理解。所提出的方法使用非真实感渲染(NPR)技术来提取轮廓、暗示性轮廓、暗示性高光、山脊和山谷等特征。为了将不同的特征类型映射到采样密度,我们还对特征对最终图像质量的影响进行了评估。为了从稀疏采样数据中重建图像,我们在自适应对齐的分形模式上使用线性插值。利用这种技术,我们能够提出一种算法,保证所需的最小帧率,而不会损失太多的图像质量。我们的调度算法通过按照其相应的重要值的顺序呈现特征,直到达到时间限制,从而最大化地利用每个给定的时间片。我们演示了如何使用我们的方法来提高和保证由几何和体积数据组成的复杂的基于光线的环境中的渲染时间。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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