论文标题
研究流媒体视频经验质量的评估
Study on the Assessment of the Quality of Experience of Streaming Video
论文作者
论文摘要
HTTP上的动态自适应流提供了大多数多媒体服务的工作，但是，这项技术的性质进一步使评估QOE（体验质量）变得复杂。在本文中，研究了各种客观因素对流媒体视频QOE的主观估计的影响。该论文介绍了标准和手工制作的特征，显示了它们的相关性和显着性的P值。提出了基于回归和梯度提升的VQA（视频质量评估）模型，SRCC在验证子样本上达到了高达0.9647。提出的回归模型适用于应用的应用程序（无论有没有参考视频）；梯度提升回归模型是进一步改进质量估计模型的观点。到目前为止，我们采用SQOE-III数据库，是同类产品中最大，最现实的。 VQA（视频质量评估）模型可在https://github.com/aleksandrivchenko/qoe-assesment上获得
Dynamic adaptive streaming over HTTP provides the work of most multimedia services, however, the nature of this technology further complicates the assessment of the QoE (Quality of Experience). In this paper, the influence of various objective factors on the subjective estimation of the QoE of streaming video is studied. The paper presents standard and handcrafted features, shows their correlation and p-Value of significance. VQA (Video Quality Assessment) models based on regression and gradient boosting with SRCC reaching up to 0.9647 on the validation subsample are proposed. The proposed regression models are adapted for applied applications (both with and without a reference video); the Gradient Boosting Regressor model is perspective for further improvement of the quality estimation model. We take SQoE-III database, so far the largest and most realistic of its kind. The VQA (video quality assessment) models are available at https://github.com/AleksandrIvchenko/QoE-assesment
