Traffic models for H.264 video using hierarchical prediction structures

Akshay Pulipaka, Patrick Seeling, Martin Reisslein

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

3 Scopus citations

Abstract

We present different video traffic models for H.264 variable bit rate (VBR) videos. We propose our models on top of the recent unified traffic model developed by Dai et al. [1], which presents a frame-level hybrid framework for modeling MPEG-4 and H.264 multi-layer VBR video traffic. We exploit the hierarchical predication structure inherent in H.264 for intra-GoP (group of pictures) analysis. We model the children frames by considering various combinations of the correlation between the parent frames in the prediction structure. Our simulations show that modeling using the hierarchical prediction structure indeed improves capturing the statistical features of the videos and prediction of network performance, without an increase in the complexity as compared to the unified traffic model by Dai et al. [1], which was shown earlier to be better than previous traffic models.

Original languageEnglish (US)
Title of host publication2012 IEEE Global Communications Conference, GLOBECOM 2012
Pages2107-2112
Number of pages6
DOIs
StatePublished - Dec 1 2012
Event2012 IEEE Global Communications Conference, GLOBECOM 2012 - Anaheim, CA, United States
Duration: Dec 3 2012Dec 7 2012

Publication series

NameGLOBECOM - IEEE Global Telecommunications Conference

Other

Other2012 IEEE Global Communications Conference, GLOBECOM 2012
CountryUnited States
CityAnaheim, CA
Period12/3/1212/7/12

Keywords

  • H.264 SVC
  • Hierarchical prediction structures
  • intra-GoP correlation
  • video traffic modeling

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

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