Compact tetrahedralization-based acceleration structures for ray tracing
Compact tetrahedralization-based acceleration structures for ray tracing
复制标题
用于光线追踪的紧凑四面体加速结构
DOI：
10.1007/s12650-022-00842-x
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发表时间：
2021
影响因子：
1.7
通讯作者：
U. Güdükbay
中科院分区：
文献类型：
--
作者：
Aytek Aman;S. Demirci;U. Güdükbay
我们提出了紧凑和高效的四面体网格表示，以提高光线跟踪性能。我们重新排序四面体网格数据使用空间填充曲线，以提高缓存的局部性。最重要的是，我们提出了有效的光线遍历算法。我们提供的细节，定期光线跟踪操作的四面体网格和GPU实现我们的遍历方法。我们通过一系列综合实验来证明我们的发现。我们的方法优于现有的四面体网格为基础的遍历方法，并产生可比的结果的遍历方法的基础上的最先进的加速结构，如k维（k-d）树和包围体层次（BVH）的速度。在计算方面，我们的方法比基于四面体网格的方法使用更少的内存，从而允许在GPU上渲染更大的场景。
We propose compact and efficient tetrahedral mesh representations to improve the ray-tracing performance. We reorder tetrahedral mesh data using a space-filling curve to improve cache locality. Most importantly, we propose efficient ray-traversal algorithms. We provide details of the regular ray-tracing operations on tetrahedral meshes and the GPU implementation of our traversal method. We demonstrate our findings through a set of comprehensive experiments. Our method outperforms existing tetrahedral mesh-based traversal methods and yields comparable results to the traversal methods based on the state-of-the-art acceleration structures such as k-dimensional (k-d) tree and Bounding Volume Hierarchy (BVH) in terms of speed. Storage-wise, our method uses less memory than its tetrahedral mesh-based counterparts, thus allowing larger scenes to be rendered on the GPU.
影响因子：
6.2
作者：
Hu, Yixin;Zhou, Qingnan;Panozzo, Daniele
通讯作者：
Panozzo, Daniele