使用ITU-T rec. P. 1203的HTTP自适应流QoE估计:开放数据库和软件

W. Robitza, Steve Goering, A. Raake, David Lindero, Gunnar Heikkilä, Jorgen Gustafsson, P. List, B. Feiten, Ulf Wüstenhagen, Marie-Neige Garcia, Kazuhisa Yamagishi, S. Broom
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引用次数: 102

摘要

本文描述了ITU-T Ree的开放数据集和软件。P.1203。作为视听HTTP自适应流(HAS)的第一个标准化的体验质量模型,它已经在超过一千个包含HAS典型效果(如失速,编码工件,质量切换)的视听序列上进行了广泛的训练和验证。我们的数据集包括比特流特征级别的30个官方主观数据库中的4个。本文还包括主观结果和模型性能。我们的标准软件也向公众开放,它被用于所有的分析。在其他先前未发表的细节中,我们展示了使用基于比特流的模型比基于元数据的模型进行视频质量分析的显着性能改进,以及将经典模型与基于机器学习的方法相结合用于估计用户QoE的鲁棒性。
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HTTP adaptive streaming QoE estimation with ITU-T rec. P. 1203: open databases and software
This paper describes an open dataset and software for ITU-T Ree. P.1203. As the first standardized Quality of Experience model for audiovisual HTTP Adaptive Streaming (HAS), it has been extensively trained and validated on over a thousand audiovisual sequences containing HAS-typical effects (such as stalling, coding artifacts, quality switches). Our dataset comprises four of the 30 official subjective databases at a bitstream feature level. The paper also includes subjective results and the model performance. Our software for the standard was made available to the public, too, and it is used for all the analyses presented. Among other previously unpublished details, we show the significant performance improvements of using bitstream-based models over metadata-based ones for video quality analysis, and the robustness of combining classical models with machine-learning-based approaches for estimating user QoE.
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