Fast and reliable decimation of polygonal models based on volume and normal field

  • Authors:
  • Muhammad Hussain

  • Affiliations:
  • Department of Computer Science, College of Computer and Information Science, King Saud University, KSA

  • Venue:
  • ISVC'10 Proceedings of the 6th international conference on Advances in visual computing - Volume Part I
  • Year:
  • 2010

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Abstract

Fast, reliable, and feature preserving automatic decimation of polygonal models is a challenging task. Exploiting both local volume and normal field variations in a novel way, a two phase decimation algorithm is proposed. In the first phase, a vertex is selected randomly using the measure of geometric fidelity that is based on normal field variation across its one-ring neighborhood. The selected vertex is eliminated in the second phase by collapsing an outgoing half-edge that is chosen by using volume based measure of geometric deviation. The proposed algorithm not only has better speed-quality trade-off but also keeps visually important features even after drastic simplification in a better way than similar state-of-the-art best algorithms; subjective and objective comparisons validate the assertion. This method can simplify huge models efficiently and is useful for applications where computing coordinates and/or attributes other than those attached to the original vertices is not allowed by the application and the focus is on both speed and quality of LODs.