Efficient fine-granular scalable coding of 3D mesh sequences

Jae Kyun Ahn, Yeong Jun Koh, Chang-Su Kim

Research output: Contribution to journalArticlepeer-review

23 Citations (Scopus)


An efficient fine-granular scalable coding algorithm of 3-D mesh sequences for low-latency streaming applications is proposed in this work. First, we decompose a mesh sequence into spatial and temporal layers to support scalable decoding. To support the finest-granular spatial scalability, we decimate only a single vertex at each layer to obtain the next layer. Then, we predict the coordinates of decimated vertices spatially and temporally based on a hierarchical prediction structure. Last, we quantize and transmit the spatio-temporal prediction residuals using an arithmetic coder. We propose an efficient context model for the arithmetic coding. Experiment results show that the proposed algorithm provides significantly better compression performance than the conventional algorithms, while supporting finer-granular spatial scalability.

Original languageEnglish
Article number6387603
Pages (from-to)485-497
Number of pages13
JournalIEEE Transactions on Multimedia
Issue number3
Publication statusPublished - 2013 Apr


  • 3D mesh coding
  • Entropy coding
  • Fine-granular scalability
  • Mesh sequence compression
  • Predictive coding
  • Spatial layer decomposition

ASJC Scopus subject areas

  • Signal Processing
  • Media Technology
  • Computer Science Applications
  • Electrical and Electronic Engineering


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