Subjective analysis and objective characterization of adaptive bitrate videos

Abstract

The HTTP Adaptive Streaming (HAS) technology allows video service providers to improve the network utilization and thereby increasing the end-users’ Quality of Experience (QoE). This has made HAS a widely used approach for audiovisual delivery. There are several previous studies aiming to identify the factors influencing on subjective QoE of adaptation events. However, adapting the video quality typically lasts in a time scale much longer than what current standardized subjective testing methods are designed for, thus making the full matrix design of the experiment on an event level hard to achieve. In this study, we investigated the overall subjective QoE of 6 minutes long video sequences containing different sequential adaptation events. This was compared to a dataset from our previous work performed to evaluate the individual adaptation events. We could then derive a relationship between the overall mean opinion score (MOS) and the MOS from shorter sequences. The aforementioned empirical dataset has proven to be very challenging in terms of video quality assessment test design, thus deriving a conclusive outcome about the influence of different parameters have been difficult. The second contribution of this study is considering how objective characterizations of adapted videos can improve the understanding of the subjective ratings.