Real-Time Continuous Level of Detail Rendering of Point Clouds

Information

• Publication Type: Conference Paper
• Workgroup(s)/Project(s):
  • Rendering and Modeling
  • VRVis Competence Center
• Date: March 2019
• Publisher: IEEE
• Location: Osaka, Japan
• Lecturer: Markus Schütz
• Event: IEEE VR 2019, the 26th IEEE Conference on Virtual Reality and 3D User Interfaces
• DOI: 10.1109/VR.2019.8798284
• Call for Papers: Call for Paper
• Booktitle: 2019 IEEE Conference on Virtual Reality and 3D User Interfaces
• Conference date: 23. March 2019 – 27. March 2019
• Pages: 103 – 110
• Keywords: point clouds, virtual reality, VR

Abstract

Real-time rendering of large point clouds requires acceleration structures that reduce the number of points drawn on screen. State-of-the art algorithms group and render points in hierarchically organized chunks with varying extent and density, which results in sudden changes of density from one level of detail to another, as well as noticeable popping artifacts when additional chunks are blended in or out. These popping artifacts are especially noticeable at lower levels of detail, and consequently in virtual reality, where high performance requirements impose a reduction in detail.

We propose a continuous level-of-detail method that exhibits gradual rather than sudden changes in density. Our method continuously recreates a down-sampled vertex buffer from the full point cloud, based on camera orientation, position, and distance to the camera, in a point-wise rather than chunk-wise fashion and at speeds up to 17 million points per millisecond. As a result, additional details are blended in or out in a less noticeable and significantly less irritating manner as compared to the state of the art. The improved acceptance of our method was successfully evaluated in a user study.

Additional Files and Images

Weblinks

• Essential source code samples
• DOI: 10.1109/VR.2019.8798284

BibTeX

@inproceedings{schuetz-2019-CLOD,
  title =      "Real-Time Continuous Level of Detail Rendering of Point
               Clouds",
  author =     "Markus Sch\"{u}tz and Katharina Kr\"{o}sl and Michael Wimmer",
  year =       "2019",
  abstract =   "Real-time rendering of large point clouds requires
               acceleration structures that reduce the number of points
               drawn on screen. State-of-the art algorithms group and
               render points in hierarchically organized chunks with
               varying extent and density, which results in sudden changes
               of density from one level of detail to another, as well as
               noticeable popping artifacts when additional chunks are
               blended in or out.  These popping artifacts are especially
               noticeable at lower levels of detail, and consequently in
               virtual reality, where high performance requirements impose
               a reduction in detail.  We propose a continuous
               level-of-detail method that exhibits gradual rather than
               sudden changes in density. Our method continuously recreates
               a down-sampled vertex buffer from the full point cloud,
               based on camera orientation, position, and distance to the
               camera, in a point-wise rather than chunk-wise fashion and
               at speeds up to 17 million points per millisecond. As a
               result, additional details are blended in or out in a less
               noticeable and significantly less irritating manner as
               compared to the state of the art. The improved acceptance of
               our method was successfully evaluated in a user study.",
  month =      mar,
  publisher =  "IEEE",
  location =   "Osaka, Japan",
  event =      "IEEE VR 2019, the 26th IEEE Conference on Virtual Reality
               and 3D User Interfaces",
  doi =        "10.1109/VR.2019.8798284",
  booktitle =  "2019 IEEE Conference on Virtual Reality and 3D User
               Interfaces",
  pages =      "103--110",
  keywords =   "point clouds, virtual reality, VR",
  URL =        "https://www.cg.tuwien.ac.at/research/publications/2019/schuetz-2019-CLOD/",
}