Pause Intensity: A No-Reference Quality Assessment Metric for Video Streaming in TCP Networks

Colin Bailey, Mirghiasaldin Seyedebrahimi, Xiaohong Peng
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引用次数: 10

Abstract

In this paper a full analytic model for pause intensity (PI), a no-reference metric for video quality assessment, is presented. The model is built upon the video play out buffer behavior at the client side and also encompasses the characteristics of a TCP network. Video streaming via TCP produces impairments in play continuity, which are not typically reflected in current objective metrics such as PSNR and SSIM. Recently the buffer under run frequency/probability has been used to characterize the buffer behavior and as a measurement for performance optimization. But we show, using subjective testing, that under run frequency cannot reflect the viewers' quality of experience for TCP based streaming. We also demonstrate that PI is a comprehensive metric made up of a combination of phenomena observed in the play out buffer. The analytical model in this work is verified with simulations carried out on ns-2, showing that the two results are closely matched. The effectiveness of the PI metric has also been proved by subjective testing on a range of video clips, where PI values exhibit a good correlation with the viewers' opinion scores.
暂停强度:TCP网络中视频流的无参考质量评估指标
本文提出了视频质量评价的无参考指标——暂停强度(PI)的全解析模型。该模型建立在客户端视频播放缓冲区行为的基础上,并且还包含了TCP网络的特征。通过TCP传输的视频流会对播放连续性造成损害,这通常不会反映在当前的客观指标(如PSNR和SSIM)中。最近,缓冲区在运行频率/概率下被用来描述缓冲区的行为,并作为性能优化的度量。但我们表明,使用主观测试,运行频率不能反映观众的体验质量为TCP为基础的流。我们还证明PI是一个综合指标,由在发挥缓冲中观察到的现象组合组成。在ns-2上进行了仿真,验证了本文的分析模型,结果表明两者吻合较好。对一系列视频剪辑的主观测试也证明了PI度量的有效性,其中PI值与观众的意见得分表现出良好的相关性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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