Marie-Neige Garcia

TL;DR: The concepts and ideas cited in this paper mainly refer to the Quality of Experience of multimedia communication systems, but may be helpful also for other areas where QoE is an issue, and the document will not reflect the opinion of each individual person at all points.

TL;DR: This paper describes an open dataset and software for ITU-T Ree, the first standardized Quality of Experience model for audiovisual HTTP Adaptive Streaming, and shows the significant performance improvements of using bitstream-based models over metadata-based ones for video quality analysis, and the robustness of combining classical models with machine-learning-based approaches for estimating user QoE.

TL;DR: The scalable video quality model part of the P.1203 Recommendation series, developed in a competition within ITU-T Study Group 12 previously referred to as P.NATS, provides integral quality predictions for 1 up to 5 min long media sessions for HTTP Adaptive Streaming with up to HD video resolution.

TL;DR: In this article, a method and an apparatus for estimating a quality of an audio-video signal includes calculating audio and video quality factors from audio and visual technical characteristics, such as audio quality, video quality and audio visual quality.

TL;DR: This article reviews the different quality models that exploit packet- header-, bit stream-, or signal-information for providing audio, video, and audiovisual quality estimates, respectively and describes how these models can be applied for real-life monitoring, and how they can be adapted to reflect the information available at the given measurement point.