Automatic QoE evaluation for asymmetric encoding of 3D videos for DASH streaming service


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The paper is based on the study of the performance of a Dynamic Adaptive Streaming over HTTP (DASH) system in the context of 3D video streaming, using different scenarios and network conditions, specifically with bandwidth variations. The objective is the development of a framework for the evaluation of QoE in 3D adaptive video streaming scenarios, which allows to analyze the impact on the user’s Quality of Experience (QoE) using different bandwidth variation patterns (switching frequency, range and type of variation), among other aspects. A set of subjective tests will be carried out, with the aim of identifying the correlation between the quality of the user experience and the frequency, type, range and temporal location of the bandwidth switching events. The proposed framework allows performance measurements to be carried out in an automated and systematic way for the evaluation of DASH systems in 2D and 3D video streaming service. We have used Puppeteer, the Node.js library developed by Google, which provides a high-level API, to automate actions on Chrome Devtools Protocol, such as starting playback, causing bandwidth changes and saving the results of quality change processes, timestamps, stalls and so on. From this data, a processing is made to allow the reconstruction of the visualized video, as well as the extraction of quality metrics and the users’ QoE assessment using the ITU-T P.1203 recommendation.

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