Efficient Fine-Granular Scalable Coding of 3D Mesh Sequences

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 decima...

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Bibliographic Details
Published in:IEEE transactions on multimedia Vol. 15; no. 3; pp. 485 - 497
Main Authors: Ahn, Jae-Kyun, Koh, Yeong Jun, Kim, Chang-Su
Format: Journal Article
Language:English
Published: New York, NY IEEE 01.04.2013
Institute of Electrical and Electronics Engineers
Subjects:
3D mesh coding
Algorithm design and analysis
Algorithmics. Computability. Computer arithmetics
Applied sciences
Artificial intelligence
Coding, codes
Computer science; control theory; systems
Computer systems and distributed systems. User interface
Encoding
entropy coding
Exact sciences and technology
fine-granular scalability
Information, signal and communications theory
mesh sequence compression
Pattern recognition. Digital image processing. Computational geometry
Prediction algorithms
predictive coding
Principal component analysis
Scalability
Signal and communications theory
Software
spatial layer decomposition
Telecommunications and information theory
Theoretical computing
Topology
Vectors
Streaming
Arithmetics
Scalability
entropy coding
Video signal
Lossless compression
Entropy codes
spatial layer decomposition
Image compression
Decoding
3D mesh coding
Delay
fine-granular scalability
mesh sequence compression
Image coding
Predictive coding
Tridimensional image
Hierarchical system
Arithmetic model
Variable length code
Mesh generation
ISSN:1520-9210, 1941-0077
Online Access:Get full text
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Description
Summary: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.
ISSN:1520-9210
1941-0077
DOI:10.1109/TMM.2012.2235417