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Proceedings of the 12th annual ACM international conference on Multimedia
Quality monitoring for compressed video subjected to packet loss
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IEEE Transactions on Multimedia
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Path selection using available bandwidth estimation in overlay-based video streaming
Computer Networks: The International Journal of Computer and Telecommunications Networking
Real-time monitoring of video quality in IP networks
IEEE/ACM Transactions on Networking (TON)
Modeling and analysis of distortion caused by Markov-model burst packet losses in video transmission
IEEE Transactions on Circuits and Systems for Video Technology
No-reference video quality monitoring for H.264/AVC coded video
IEEE Transactions on Multimedia
Improved min-cost flow scheduler for mesh-based P2P streaming system
ICME'09 Proceedings of the 2009 IEEE international conference on Multimedia and Expo
A versatile model for packet loss visibility and its application to packet prioritization
IEEE Transactions on Image Processing
Path selection using available bandwidth estimation in overlay-based video streaming
NETWORKING'07 Proceedings of the 6th international IFIP-TC6 conference on Ad Hoc and sensor networks, wireless networks, next generation internet
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Network assessment for low bitrate video
Sarnoff'10 Proceedings of the 33rd IEEE conference on Sarnoff
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IEEE/ACM Transactions on Networking (TON)
Q-score: proactive service quality assessment in a large IPTV system
Proceedings of the 2011 ACM SIGCOMM conference on Internet measurement conference
Video qos monitoring and control framework over mobile and IP networks
PCM'06 Proceedings of the 7th Pacific Rim conference on Advances in Multimedia Information Processing
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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.