GPU‐Accelerated LOD Generation for Point Clouds

Information

• Publication Type: Journal Paper with Conference Talk
• Workgroup(s)/Project(s):
  • Efficient workflow transforming large 3D point clouds to Building Information Models with user-assisted automatization
• Date: June 2023
• Journal: Computer Graphics Forum
• Volume: 42
• Open Access: yes
• Number: 8
• Location: Delft
• Lecturer: Markus Schütz
• Article Number: e14877
• ISSN: 1467-8659
• Event: High Performance Graphics
• DOI: 10.1111/cgf.14877
• Pages: 12
• Publisher: WILEY
• Conference date: 2023
• Pages: 1 – 12
• Keywords: point cloud rendering, level of detail, LOD

Abstract

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.

Additional Files and Images

Weblinks

• Source Code
• Entry in reposiTUm (TU Wien Publication Database)
• DOI: 10.1111/cgf.14877

BibTeX

@article{SCHUETZ-2023-LOD,
  title =      "GPU‐Accelerated LOD Generation for Point Clouds",
  author =     "Markus Sch\"{u}tz and Bernhard Kerbl and Philip Klaus and
               Michael Wimmer",
  year =       "2023",
  abstract =   "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.",
  month =      jun,
  journal =    "Computer Graphics Forum",
  volume =     "42",
  number =     "8",
  articleno =  "e14877",
  issn =       "1467-8659",
  doi =        "10.1111/cgf.14877",
  pages =      "12",
  publisher =  "WILEY",
  pages =      "1--12",
  keywords =   "point cloud rendering, level of detail, LOD",
  URL =        "https://www.cg.tuwien.ac.at/research/publications/2023/SCHUETZ-2023-LOD/",
}