Adaptive Streaming: A subjective catalog to assess the performance of objective QoE metrics

Alberto Álvarez, Laura Pozueco, Sergio Cabrero, Xabiel García Pañeda, Roberto García, David Melendi, Gabriel Díaz Orueta


Scalable streaming has emerged as a feasible solution to resolve users' heterogeneity problems. SVC is the technology that has served as the definitive impulse for the growth of streaming adaptive systems. Systems seek to improve layer switching efficiency from the network point of view but, with increasing importance, without jeopardizing user perceived video quality, i.e., QoE. We have performed extensive subjective experiments to corroborate the preference towards adaptive systems when compared to traditional non-adaptive systems. The resulting subjective scores are correlated with most relevant Full Reference (FR) objective metrics. We obtain an exponential relationship between human decisions and the same decisions expressed as a difference of objective metrics. A strong correlation with subjective scores validates objective metrics to be used as aid in the adaptive decision taking algorithms to improve overall systems performance. Results show that, among the evaluated objective metrics, PSNR is the metric that provide worse results in terms of reproducing the human decisions.


Adaptive streaming; Scalable Video Coding (SVC); objective video quality metrics; subjective quality assessment

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