3D mesh compression based on dual-ring prediction and MMSE prediction

Dae Youn Lee, Jae Kyun Ahn, Minsu Ahn, James D K Kim, Changyeong Kim, Chang-Su Kim

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)

Abstract

A three-dimensional (3D) mesh compression algorithm based on novel prediction methods and a mode decision scheme is proposed in this work. After decomposing an input mesh into base and refinement layers, we segment the geometry data of each layer into clusters. To encode vertex positions efficiently, we propose two prediction methods: the dual ring prediction and the minimum mean square error (MMSE) prediction. Also, we develop a mode decision scheme that selects the best prediction mode for each cluster. Simulation results demonstrate that the proposed algorithm provides significantly better compression performance than conventional techniques.

Original languageEnglish
Title of host publicationICIP 2011
Subtitle of host publication2011 18th IEEE International Conference on Image Processing
Pages905-908
Number of pages4
DOIs
Publication statusPublished - 2011
Event2011 18th IEEE International Conference on Image Processing, ICIP 2011 - Brussels, Belgium
Duration: 2011 Sep 112011 Sep 14

Publication series

NameProceedings - International Conference on Image Processing, ICIP
ISSN (Print)1522-4880

Other

Other2011 18th IEEE International Conference on Image Processing, ICIP 2011
CountryBelgium
CityBrussels
Period11/9/1111/9/14

Keywords

  • 3D mesh compression
  • geometry coding
  • mode decision
  • predictive coding
  • progressive mesh compression

ASJC Scopus subject areas

  • Software
  • Computer Vision and Pattern Recognition
  • Signal Processing

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  • Cite this

    Lee, D. Y., Ahn, J. K., Ahn, M., Kim, J. D. K., Kim, C., & Kim, C-S. (2011). 3D mesh compression based on dual-ring prediction and MMSE prediction. In ICIP 2011: 2011 18th IEEE International Conference on Image Processing (pp. 905-908). [6116706] (Proceedings - International Conference on Image Processing, ICIP). https://doi.org/10.1109/ICIP.2011.6116706