Framework for the integrated video quality assessment

Authors:
Mu Mu;Piotr Romaniak;Andreas Mauthe;Mikołaj Leszczuk;Lucjan Janowski;Eduardo Cerqueira
Affiliations:
The School of Computing and Communications, Lancaster University, Lancaster, UK;The Department of Telecommunications, AGH University of Science and Technology, Krakow, Poland;The School of Computing and Communications, Lancaster University, Lancaster, UK;The Department of Telecommunications, AGH University of Science and Technology, Krakow, Poland;The Department of Telecommunications, AGH University of Science and Technology, Krakow, Poland;The Federal University of Para, Belem, Brazil
Venue:
Multimedia Tools and Applications
Year:
2012

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Abstract

Through years of development Content Networks (CN) have become more sophisticated and more technically diverse. Modern CN are designed to be more adaptive to communication environment, devices and user requirements. However, one open issue is the still fluctuating quality of service provision. As a result user experience can be negatively affected. In order to maintain a satisfactory level of user experience it is crucial to develop a feasible solution to measure the extent to which video services meet users' expectation. Assessing video quality with respect to users' subjective opinions is a complex task. In this paper we address challenges of this task and design an integrated framework using a number of comprehensive functional modules. Our framework integrates objective quality assessment models of Artifacts Measurement (AM) and Quality of Delivery (QoD) approaches. Only the fittest models are activated by the framework considering requirements of individual evaluation tasks. We also introduce our recent work of realising key functional modules of the framework. Joint subjective experiments between two institutes have also been carried out for the purpose of model implementation and evaluation. Results from experiments verify the concept of an integrated framework and show the effectiveness of its key modules in estimating the quality level of video services.