Quantifying subjective quality evaluations for mobile video watching in a semi-living lab context

This paper discusses results from an exploratory study in which Quality of Experience aspects related to mobile video watching were investigated in a semi-living lab setting. More specifically, we zoom in on usage patterns in a natural research context and on the subjective evaluation of high and low-resolution movie trailers that are transferred to a mobile device using two transmission protocols for video (i.e., real-time transport protocol and progressive download using HTTP). User feedback was collected by means of short questionnaires on the mobile device, combined with traditional pen and paper diaries. The subjective evaluations regarding the general technical quality, perceived distortion, fluentness of the video, and loading speed are studied and the influence of the transmission protocol and video resolution on these evaluations is analyzed. Multinomial logistic regression results in a model to estimate the subjective evaluations regarding the perceived distortion and loading speed based on objectively-measured parameters of the video session

Quantifying the influence of rebuffering interruptions on the user's quality of experience during mobile video watching

Entertainment and multimedia are the key functionalities in emerging mobile markets. The ability to understand and quantify the quality of experience (QoE, i.e., the users' subjective perception of the "overall acceptability of an application or service"), will play a major role in the success of these mobile services. This study explores the thresholds at which the technical quality of a mobile video service becomes unacceptable for users. A subjective experiment drawing on the logging of technical parameters combined with subjective evaluations by a user panel resulted in a model for quantifying the acceptability of video interruptions. The results of this analysis provide insights into the QoE and (un)acceptability regarding video interruptions for different network conditions and video parameters. The conclusions of this paper can be used as a guideline for service design and network dimensioning

Video streaming

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