Information

Abstract

In this paper we present an out-of-core editing system for point clouds, which allows selecting and modifying arbitrary parts of a huge point cloud interactively. We can use the selections to segment the point cloud, to delete points, or to render a preview of the model without the points in the selections. Furthermore we allow for inserting points into an already existing point cloud. All operations are conducted on a rendering optimized data structure that uses the raw point cloud from a laser scanner, and no additionally created points are needed for an ecient level-of-detail (LOD) representation using this data structure. We also propose an algorithm to alleviate the artifacts when rendering a point cloud with large discrepancies in density in dierent areas by estimating point sizes heuristically. These estimated point sizes can be used to mimic a closed surface on the raw point cloud, also when the point cloud is composed of several raw laser scans.

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Additional images and videos

image: Selecting points image: Selecting points

Additional files

paper: Out-of-Core Selection and Editing of Huge Point Clouds paper: Out-of-Core Selection and Editing of Huge Point Clouds

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BibTeX

@article{scheiblauer-2011-cag,
  title =      "Out-of-Core Selection and Editing of Huge Point Clouds",
  author =     "Claus Scheiblauer and Michael Wimmer",
  year =       "2011",
  abstract =   "In this paper we present an out-of-core editing system for
               point clouds, which allows selecting and modifying arbitrary
               parts of a huge point cloud interactively. We can use the
               selections to segment the point cloud, to delete points, or
               to render a preview of the model without the points in the
               selections. Furthermore we allow for inserting points into
               an already existing point cloud. All operations are
               conducted on a rendering optimized data structure that uses
               the raw point cloud from a laser scanner, and no
               additionally created points are needed for an ecient
               level-of-detail (LOD) representation using this data
               structure. We also propose an algorithm to alleviate the
               artifacts when rendering a point cloud with large
               discrepancies in density in dierent areas by estimating
               point sizes heuristically. These estimated point sizes can
               be used to mimic a closed surface on the raw point cloud,
               also when the point cloud is composed of several raw laser
               scans.",
  month =      apr,
  issn =       "0097-8493",
  journal =    "Computers & Graphics",
  number =     "2",
  volume =     "35",
  pages =      "342--351",
  keywords =   "Graphics data structures and data types, Viewing algorithms,
               Point-based rendering",
  URL =        "https://www.cg.tuwien.ac.at/research/publications/2011/scheiblauer-2011-cag/",
}