Skip to main content
Log in

Detecting and reconstructing subdivision connectivity

  • Original article
  • Published:
The Visual Computer Aims and scope Submit manuscript

inverse subdivision algorithms

, with linear time and space complexity, to detect and reconstruct uniform Loop, Catmull–Clark, and Doo–Sabin subdivision structure in irregular triangular, quadrilateral, and polygonal meshes. We consider two main applications for these algorithms. The first one is to enable interactive modeling systems that support uniform subdivision surfaces to use popular interchange file formats which do not preserve the subdivision structure, such as VRML, without loss of information. The second application is to improve the compression efficiency of existing lossless connectivity compression schemes, by optimally compressing meshes with Loop subdivision connectivity. Our Loop inverse subdivision algorithm is based on global connectivity properties of the covering mesh, a concept motivated by the covering surface from Algebraic Topology. Although the same approach can be used for other subdivision schemes, such as Catmull–Clark, we present a Catmull–Clark inverse subdivision algorithm based on a much simpler graph-coloring algorithm and a Doo–Sabin inverse subdivision algorithm based on properties of the dual mesh. Straightforward extensions of these approaches to other popular uniform subdivision schemes are also discussed.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

Author information

Authors and Affiliations

Authors

Additional information

Published online: 3 July 2002

Rights and permissions

Reprints and permissions

About this article

Cite this article

Taubin, G. Detecting and reconstructing subdivision connectivity. Visual Comp 18, 357–367 (2002). https://doi.org/10.1007/s003710100152

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s003710100152

Navigation