Study on Viewing Time with Regards to Quality Factors in Adaptive Bitrate Video Streaming

2018 IEEE 20th International Workshop on Multimedia Signal Processing (MMSP) Pub Date : 2018-08-01 DOI:10.1109/MMSP.2018.8547057

Pierre R. Lebreton, Kimiko Kawashima, Kazuhisa Yamagishi, J. Okamoto

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引用次数: 8

Abstract

In this work, the evaluation of user engagement's characteristics in adaptive bitrate video streaming is addressed. To this aim, the viewing time and its relation with video quality is studied in two carefully designed subjective tests. Video quality and viewing time were addressed in distinct experiments. In case of viewing time, users were allowed to stop watching the videos when they desired. It was found that for low-quality videos, the number of users dropping the video increases logarithmically as a function of time. In addition, when a stalling event occurs, users start dropping video playback after a waiting period of 5 seconds. Then, when the stalling ends, the dropping rate returns to its baseline rate (which depends on video quality). The number of users stopping watching video after a stalling event was found to be a function of stalling position, stalling duration, and the quality affected by coding. A baseline model considering only stalling features is defined. Finally, a model for predicting the video completion rate is proposed that achieves a Pearson correlation of 0.96 and a root-mean-square error (RMSE) of 0.064.

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自适应比特率视频流中考虑质量因素的观看时间研究

在这项工作中，讨论了自适应比特率视频流中用户参与特性的评估。为此，在两个精心设计的主观测试中，研究了观看时间及其与视频质量的关系。视频质量和观看时间在不同的实验中得到解决。在观看时间方面，用户可以随时停止观看视频。研究发现，对于低质量的视频，放弃视频的用户数量作为时间的函数呈对数增长。此外，当发生失速事件时，用户在等待5秒后开始播放视频。然后，当失速结束时，下降率返回到其基线率(这取决于视频质量)。发现失速事件后停止观看视频的用户数量与失速位置、失速时长和编码对视频质量的影响有关。定义了只考虑失速特征的基线模型。最后，提出了一个预测视频完成率的模型，Pearson相关系数为0.96，均方根误差(RMSE)为0.064。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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2018 IEEE 20th International Workshop on Multimedia Signal Processing (MMSP)

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