Abstract

In addition to traditional Quality of Service (QoS), Quality of Experience (QoE) poses a real challenge for Internet service providers, audio-visual services, broadcasters and new Over-The-Top (OTT) services. Therefore, objective audio-visual metrics are frequently being dedicated in order to monitor, troubleshoot, investigate and set benchmarks of content applications working in real-time or off-line. The concept proposed here, Monitoring of Audio Visual Quality by Key Performance Indicators (MOAVI), is able to isolate and focus investigation, set-up algorithms, increase the monitoring period and guarantee better prediction of perceptual quality. MOAVI artefacts Key Performance Indicators (KPI) are classified into four categories, based on their origin: capturing, processing, transmission, and display. In the paper, we present experiments carried out over several steps with four experimental set-ups for concept verification. The methodology takes into the account annoyance visibility threshold. The experimental methodology is adapted from International Telecommunication Union – Telecommunication Standardization Sector (ITU-T) Recommendations: P.800, P.910 and P.930. We also present the results of KPI verification tests. Finally, we also describe the first implementation of MOAVI KPI in a commercial product: the NET-MOZAIC probe. Net Research, LLC, currently offers the probe as a part of NET-xTVMS Internet Protocol Television (IPTV) and Cable Television (CATV) monitoring system.

Highlights

  • In addition to traditional Quality of Service (QoS), Quality of Experience (QoE) poses a real challenge for Internet service providers, audiovisual services, broadcasters, and new OverThe-Top (OTT) services

  • Objective audiovisual metrics are frequently dedicated to monitoring, troubleshooting, investigating, and setting benchmarks of content applications working in real-time or off-line

  • The probe is offered by Net Research, LLC as part of NET-xTVMS Internet Protocol Television (IPTV) and Cable Television (CATV) monitoring systems

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Summary

Introduction

In addition to traditional Quality of Service (QoS), Quality of Experience (QoE) poses a real challenge for Internet service providers, audiovisual services, broadcasters, and new OverThe-Top (OTT) services. The classic quality metric approach cannot provide pertinent predictive scores with a quantitative description of specific (new) audiovisual artefacts, such as stripe error or exposure distortions. In realistic situations, when video quality decreases in audiovisual services, customers can call a helpline to describe the annoyance and visibility of the defects or degradations in order to describe the outage. They are not required to provide a Mean Opinion Score (MOS). We present our experiments carried out over several steps with four experimental set-ups for concept verification.

State-of-the-art background
Capturing
Processing
Transmission
Display
Exposure time
Block loss
Blocking
Freezing
Slicing
Experimental set-ups for concept verification
CONTENT 2009 experimental setup
VQEG HDTV 2010 experimental setup
INDECT 2011 experimental setup
VARIUM 2013 experimental setup
Results of KPI
Setting the metric threshold values
KPI verification
Deployment
NET-MOZAIC probe description
Functional diagram
Key features
MOAVI KPI metrics implemented in the NET-MOZAIC
NET-MOZAIC in the NET-xTVMS system
Conclusions and future work
14. International Telecommunication Union
Full Text
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