Let me Decrypt your Beauty: Real-time Prediction of Video Resolution and Bitrate for Encrypted Video Streaming
Let me Decrypt your Beauty: Real-time Prediction of Video Resolution and Bitrate for Encrypted Video Streaming
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让我解密你的美丽：实时预测加密视频流的视频分辨率和码率
DOI：
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发表时间：
2019
期刊：
影响因子：
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通讯作者：
Kuang Li
中科院分区：
文献类型：
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作者：
Sarah Wassermann;Michael Seufert;P. Casas;Li Gang;Kuang Li
HTTP 自适应流媒体 (HAS) 技术引发的视频质量动态适应引入了重新缓冲之外的新体验质量 (QoE) 指标。在这项工作中，我们解决了 HAS 的实时 QoE 监控问题，重点关注针对 YouTube 的特定情况的视频分辨率和平均视频比特率的连续预测。通过对大型视频数据集的实证评估，我们证明可以实时准确地预测特定视频分辨率以及平均视频比特率，并且使用小至每秒一个新预测的时间粒度，这是文献中其他提案无法实现的。
The dynamic adaptation of the video quality induced by HTTP Adaptive Streaming (HAS) technology introduces new Quality of Experience (QoE) metrics beyond re-buffering. In this work we address the problem of real-time QoE monitoring of HAS, focusing on the continuous prediction of video resolution and average video bitrate, for the particular case of YouTube. Through empirical evaluations over a large video dataset, we demonstrate that it is possible to accurately predict the specific video resolution, as well as the average video bitrate, both in real time, and using a time granularity as small as one new prediction every second, not achieved by other proposals in the literature.