SRDH:专门的BVH结构和遍历顺序使用代表性的阴影射线集

Nicolas Feltman, Minjae Lee, K. Fatahalian
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引用次数: 14

摘要

我们推导了阴影射线分布启发式算法(SRDH),它是阴影射线通过边界体层次(BVH)遍历的精确成本估计器。SRDH利用先前跟踪阴影光线的分布和相交结果的预先知识来构建一个专门针对阴影光线的BVH,并选择一个相关的遍历顺序策略,通过快速发现遮挡来共同促进早期终止。在包含大量遮挡的场景中,与通过sah构建的树的平均情况遍历相比,SRDH减少了阴影计算所需的BVH节点遍历步骤的22%至56%。使用从场景的16 × 16像素渲染中记录的稀疏阴影光线集来评估SRDH,一致地产生bvh,其遍历成本在构建时所有阴影光线可用时的构建成本的6%以内。SRDH的好处是在内存中存储额外的BVH和BVH构建时间(平均)增加2.4倍。
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SRDH: specializing BVH construction and traversal order using representative shadow ray sets
We derive the Shadow Ray Distribution Heuristic (SRDH), an accurate cost estimator for shadow ray traversal through a bounding volume hierarchy (BVH). The SRDH leverages up-front knowledge of the distribution and intersection results of previously traced shadow rays to construct a shadow-ray-specialized BVH and choose an associated traversal order policy which together promote early termination by quickly finding occlusions. In scenes containing large amounts of occlusion, SRDH reduces the number of BVH node traversal steps needed for shadow computations between 22% and 56% compared to average-case traversal through SAH-constructed trees. Evaluating the SRDH using a sparse shadow ray set recorded from a 16 x16 pixel rendering of the scene consistently produces BVHs whose traversal cost is within 6% of those built when all shadow rays are available to the metric at the time of construction. The benefits of the SRDH come at the cost of storing an additional BVH in memory and a 2.4x increase (on average) in BVH construction time.
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