Framework for adaptive sampling of point-based surfaces using geometry and color attributes

  • Authors:

  • Duck Bong Kim;Eui Chul Kang;Kwan H. Lee;Renato B. Pajarola

  • Affiliations:

  • Department of Mechatronics, Gwangju Institute of Science and Technology (GIST), Intelligent Design and Graphics laboratory, Gwangju, Korea;Department of Mechatronics, Gwangju Institute of Science and Technology (GIST), Intelligent Design and Graphics laboratory, Gwangju, Korea;Department of Mechatronics, Gwangju Institute of Science and Technology (GIST), Intelligent Design and Graphics laboratory, Gwangju, Korea;Department of Informatics, Univ. of Zurich, Zurich, Switzerland

  • Venue:
  • ICCS'06 Proceedings of the 6th international conference on Computational Science - Volume Part II
  • Year:
  • 2006

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Abstract

Point-based rendering has offered a powerful alternative to triangle meshes when it comes to the rendering of highly complex objects consisting of densely sampled point clouds due to its flexibility and simplicity. The technological advance of 3D scanners has made it possible to acquire color as well as geometry data of highly complex objects. However, scanning and acquisition systems often produce surfaces that are much more dense than actually required for the intended application. Mobile devices, computer games and distributed virtual environments must often operate on systems where rendering and transmission capacity is highly constrained and therefore require strict control over the level of detail used in models. In this research, we present a framework for adaptive sampling of point-based surfaces using both geometry and color information.