Real-time monitoring of video quality in IP networks

  • Shu Tao
  • , John Apostolopoulos
  • , Roch Guérin

Research output: Contribution to conferencePaperpeer-review

41 Scopus citations

Abstract

This paper investigates the problem of assessing the quality of video transmitted over IP networks. Our goal is to develop a methodology that is both reasonably accurate and simple enough to support the large-scale deployments that the increasing use of video over IP are likely to demand. For that purpose, we focus on developing an approach that is capable of mapping network statistics, e.g., packet losses, available from simple measurements, to the quality of video sequences reconstructed by receivers. A first step in that direction is a loss-distortion model that accounts for the impact of network losses on video quality, as a function of application-specific parameters such as the video codec and loss recovery technique, coded bit rate, packetization, video characteristics, etc. The model, although accurate, is poorly suited to large-scale, on-line monitoring, because of its dependency on many parameters that are difficult to estimate in real-time. As a result, we introduce a "relative quality" metric that bypasses this problem by measuring video quality against a quality benchmark that the network is expected to provide. The approach offers a lightweight video quality monitoring solution that is suitable for large-scale deployments. We assess its feasibility and accuracy through extensive simulations and experiments.

Original languageEnglish
Pages129-134
Number of pages6
DOIs
StatePublished - 2005
Event15th International Workshop on Network and Operating Systems Support for Digital Audio and Video, NOSSDAV 2005 - Stevenson, WA, United States
Duration: Jun 13 2005Jun 14 2005

Conference

Conference15th International Workshop on Network and Operating Systems Support for Digital Audio and Video, NOSSDAV 2005
Country/TerritoryUnited States
CityStevenson, WA
Period06/13/0506/14/05

Keywords

  • Loss
  • Model
  • Video Quality

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