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Network and Content-Dependent Bitrate Ladder Estimation for Adaptive Bitrate Video Streaming

机译:自适应比特率视频流的网络和内容相关的比特率梯形图梯度估计

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In this paper, a method is presented to estimate bitrate ladders on the basis of both content complexity and network traces. Unlike previous methods, the proposed algorithm is independent of the adaptive bitrate (ABR) control scheme used by the client. The proposed approach was evaluated in a simulation on the basis of real-life throughput measurements over a large period of time and across multiple ABR control schemes. Unlike in previous studies, perceptual quality metrics that account for the effect of both coding and stalling on video quality are used in the evaluations. Results show that the proposed method performs consistently over time and across ABR control schemes. Thus, this method will enable video streaming service providers to encode videos by using their knowledge of the network performance. This will ultimately enable network usage to be optimized and the quality of experience to be improved.
机译:在本文中,提出了一种基于内容复杂性和网络迹线来估计比特率梯子的方法。 与以前的方法不同,所提出的算法独立于客户端使用的自适应比特率(ABR)控制方案。 在大型时间内和多个ABR控制方案的基础上,在模拟中评估了所提出的方法。 与先前的研究不同,在评估中使用了用于对视频质量的编码和停顿效果的感知质量指标。 结果表明,该方法随着时间的推移和ABR控制方案始终如一地执行。 因此,该方法将使视频流服务提供商能够通过使用他们对网络性能的知识来编码视频。 这将最终使网络使用能够优化和改进的经验质量。

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