About: We introduce a GPU-accelerated LOD construction process that creates a hybrid voxel-point-based variation of the widely used layered point cloud (LPC) structure for LOD rendering and streaming. The massive performance improvements provided by the GPU allow us to improve the quality of lower LODs via color filtering while still increasing construction speed compared to the non-filtered, CPU-based state of the art. Background: LOD structures are required to render hundreds of millions to trillions of points, but constructing them takes time. Results: LOD structures suitable for rendering and streaming are constructed at rates of about 1 billion points per second (with color filtering) to 4 billion points per second (sample-picking/random sampling, state of the art) on an RTX 3090 -- an improvement of a factor of 80 to 400 times over the CPU-based state of the art (12 million points per second). Due to being in-core, model sizes are limited to about 500 million points per 24GB memory. Discussion: Our method currently focuses on maximizing in-core construction speed on the GPU. Issues such as out-of-core construction of arbitrarily large data sets are not addressed, but we expect it to be suitable as a component of bottom-up out-of-core LOD construction schemes.

翻译：我们提出了一种基于GPU加速的LOD构建流程，该流程为广泛应用于分层点云（LPC）结构的LOD渲染与流式传输创建了一种混合体素-点变体方案。GPU带来的巨大性能提升使我们能够通过颜色滤波提高低层级LOD的质量，同时相比基于CPU且无滤波的现有技术，仍能提升构建速度。背景：LOD结构是渲染数亿至数万亿点云所必需的，但其构建过程耗时较长。结果：在RTX 3090上，适用于渲染与流式传输的LOD结构构建速率可达每秒约10亿点（含颜色滤波）至每秒40亿点（采样/随机采样，与现有技术相当），相比基于CPU的现有技术（每秒1200万点）提升80至400倍。由于采用内存内计算模式，模型规模受限于每24GB内存约5亿点。讨论：我们的方法当前聚焦于在GPU上最大化内存内构建速度。虽未处理大规模数据集的内存外构建等问题，但我们预期该方法可作为自底向上内存外LOD构建方案的有效组成部分。