Share Email Print

Proceedings Paper

VBR MPEG video traffic prediction based on intelligent integrated model
Author(s): Xiaoying Liu; Xiaodong Liu; Qionghai Dai; Peng Tan
Format Member Price Non-Member Price
PDF $14.40 $18.00
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

Paper Abstract

As a main video transmission mode for digital media networks, the capability to predict VBR video traffic can significantly improve the effectiveness of quality of services. Therefore, aiming at the complex characteristics of VBR MPEG videos, a novel intelligent integrated traffic prediction model is proposed based on fuzzy and neural network. The fuzzy predictor reduces the prediction error, and the implementation of neural network is used to lower the computational complexity for real-time operation. Experimental results show that the prediction errors of the proposed model are significantly smaller than the conventional AR models and provide an improved video traffic prediction technique.

Paper Details

Date Published: 24 June 2005
PDF: 8 pages
Proc. SPIE 5960, Visual Communications and Image Processing 2005, 59604U (24 June 2005); doi: 10.1117/12.633207
Show Author Affiliations
Xiaoying Liu, Tsinghua Univ. (China)
Xiaodong Liu, Tsinghua Univ. (China)
Qionghai Dai, Tsinghua Univ. (China)
Peng Tan, Tsinghua Univ. (China)

Published in SPIE Proceedings Vol. 5960:
Visual Communications and Image Processing 2005
Shipeng Li; Fernando Pereira; Heung-Yeung Shum; Andrew G. Tescher, Editor(s)

© SPIE. Terms of Use
Back to Top