Detailed Information

Cited 0 time in webofscience Cited 0 time in scopus
Metadata Downloads

Progressive 3D mesh compression using MOG-based Bayesian entropy coding and gradual prediction

Authors
Lee, Dae-YounSull, SanghoonKim, Chang-Su
Issue Date
10월-2014
Publisher
SPRINGER
Keywords
Triangular mesh; 3D mesh compression; Predictive coding; Progressive coding; Mixture of Gaussian model; Context-based arithmetic coding
Citation
VISUAL COMPUTER, v.30, no.10, pp.1077 - 1091
Indexed
SCIE
SCOPUS
Journal Title
VISUAL COMPUTER
Volume
30
Number
10
Start Page
1077
End Page
1091
URI
https://scholar.korea.ac.kr/handle/2021.sw.korea/97316
DOI
10.1007/s00371-013-0779-3
ISSN
0178-2789
Abstract
A progressive 3D triangular mesh compression algorithm built on the MOG-based Bayesian entropy coding and the gradual prediction scheme is proposed in this work. For connectivity coding, we employ MOG models to estimate the posterior probabilities of topology symbols given vertex geometries. Then, we encode the topology symbols using an arithmetic coder with different contexts, which depend on the posterior probabilities. For geometry coding, we propose the gradual prediction labeling and the dual-ring prediction to divide vertices into groups and predict later groups more efficiently using the information in already encoded groups. Simulation results demonstrate that the proposed algorithm provides significantly better performance than the conventional wavemesh coder, with the average bit rate reduction of about 16.9 %.
Files in This Item
There are no files associated with this item.
Appears in
Collections
College of Engineering > School of Electrical Engineering > 1. Journal Articles

qrcode

Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.

Related Researcher

Researcher Kim, Chang su photo

Kim, Chang su
공과대학 (전기전자공학부)
Read more

Altmetrics

Total Views & Downloads

BROWSE