A Quality-of-Experience Index for Streaming Video
A Quality-of-Experience Index for Streaming Video
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DOI：
10.1109/jstsp.2016.2608329
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发表时间：
2017-02-01
影响因子：
7.5
通讯作者：
Wang, Zhou
中科院分区：
文献类型：
--
作者：
Duanmu, Zhengfang;Zeng, Kai;Wang, Zhou
随着流媒体应用的快速增长，对体验质量（QoE）测量和QoE驱动的视频传输技术产生了强烈的需求。大多数现有方法依赖于比特率和停顿事件的全局统计数据来进行 QoE 预测。由于两个原因，这是有问题的。首先，使用相同的比特率对不同的视频内容进行编码会导致呈现质量截然不同。其次，没有考虑视频呈现质量和播放停顿体验之间的相互作用。在这项工作中，我们首先构建一个流视频数据库并进行主观用户研究，以调查人类对视频压缩、初始缓冲和停顿的综合影响的反应。然后，我们提出了一种名为流媒体 QoE 指数的新颖 QoE 预测方法，该方法考虑了由于感知视频呈现损伤、播放停顿事件以及它们之间的瞬时交互而导致的瞬时质量下降。实验结果表明，所提出的模型与主观意见非常吻合，并且显着优于现有的 QoE 模型。所提出的模型为视频流服务中的 QoE 预测提供了高效且高效的意义。
With the rapid growth of streaming media applications, there has been a strong demand of quality-of-experience (QoE) measurement and QoE-driven video delivery technologies. Most existing methods rely on bitrate and global statistics of stalling events for QoE prediction. This is problematic for two reasons. First, using the same bitrate to encode different video content results in drastically different presentation quality. Second, the interactions between video presentation quality and playback stalling experiences are not accounted for. In this work, we first build a streaming video database and carry out a subjective user study to investigate the human responses to the combined effect of video compression, initial buffering, and stalling. We then propose a novel QoE prediction approach named Streaming QoE Index that accounts for the instantaneous quality degradation due to perceptual video presentation impairment, the playback stalling events, and the instantaneous interactions between them. Experimental results show that the proposed model is in close agreement with subjective opinions and significantly outperforms existing QoE models. The proposed model provides a highly effective and efficient meanings for QoE prediction in video streaming services.