GPU-Accelerated LOD Generation for Point Clouds

Kavli Affiliate: Michael Wimmer

| First 5 Authors: Markus Sch├╝tz, Bernhard Kerbl, Philip Klaus, Michael Wimmer,

| Summary:

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.

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