具有重要采样的多视图环境遮挡

K. Vardis, Georgios Papaioannou, A. Gaitatzes
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引用次数: 30

摘要

屏幕空间环境遮挡(AO)技术已经成为实时渲染中环境光衰减和接触阴影的实际方法。尽管已经进行了广泛的研究来提高AO技术的质量和性能,但是依赖于视图的工件仍然是一个主要问题。本文介绍了多视图环境遮挡,这是一种通用的逐片段视图加权方案,用于使用多个任意视图(如现成的阴影地图)评估屏幕空间遮挡或遮挡。此外,它利用产生的权重来执行自适应采样,基于每个视图的重要性,以减少样本总数,同时保持图像质量。多视图环境遮挡改善和稳定了屏幕空间AO估计,而不会高估结果,并且可以与各种现有的屏幕空间AO技术相结合。我们用基于开体积和实体角的AO算法演示了我们的采样方法的结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Multi-view ambient occlusion with importance sampling
Screen-space ambient occlusion and obscurance (AO) techniques have become de-facto methods for ambient light attenuation and contact shadows in real-time rendering. Although extensive research has been conducted to improve the quality and performance of AO techniques, view-dependent artifacts remain a major issue. This paper introduces Multi-view Ambient Occlusion, a generic per-fragment view weighting scheme for evaluating screen-space occlusion or obscurance using multiple, arbitrary views, such as the readily available shadow maps. Additionally, it exploits the resulting weights to perform adaptive sampling, based on the importance of each view to reduce the total number of samples, while maintaining the image quality. Multi-view Ambient Occlusion improves and stabilizes the screen-space AO estimation without overestimating the results and can be combined with a variety of existing screen-space AO techniques. We demonstrate the results of our sampling method with both open volume- and solid angle-based AO algorithms.
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