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arXiv · 1311.6441

Modeling the Time-varying Subjective Quality of HTTP Video Streams with Rate Adaptations

Chao Chen·Lark Kwon Choi·Gustavo de Veciana·Constantine Caramanis·Robert W. Heath Jr.·Alan C. Bovik
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Abstract

Newly developed HTTP-based video streaming technologies enable flexible rate-adaptation under varying channel conditions. Accurately predicting the users' Quality of Experience (QoE) for rate-adaptive HTTP video streams is thus critical to achieve efficiency. An important aspect of understanding and modeling QoE is predicting the up-to-the-moment subjective quality of a video as it is played, which is difficult due to hysteresis effects and nonlinearities in human behavioral responses. This paper presents a Hammerstein-Wiener model for predicting the time-varying subjective quality (TVSQ) of rate-adaptive videos. To collect data for model parameterization and validation, a database of longer-duration videos with time-varying distortions was built and the TVSQs of the videos were measured in a large-scale subjective study. The proposed method is able to reliably predict the TVSQ of rate adaptive videos. Since the Hammerstein-Wiener model has a very simple structure, the proposed method is suitable for on-line TVSQ prediction in HTTP based streaming.

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Chao Chen, Lark Kwon Choi, Gustavo de Veciana, Constantine Caramanis, Robert W. Heath Jr., Alan C. Bovik. 2013-11-25. Modeling the Time-varying Subjective Quality of HTTP Video Streams with Rate Adaptations. https://doi.org/10.1109/tip.2014.2312613

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