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首页> 外文期刊>Motion Imaging Journal, SMPTE >ABR Quality Monitoring: State of the Art
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ABR Quality Monitoring: State of the Art

机译:ABR质量监控:最新技术

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With the move to increasingly complex adaptive bitrate technology for video transport delivery comes a corresponding increase in quality assurance complexity. Video service providers require more information than only that some number of viewers are unsatisfied with their viewing experience. More proactive warnings of deteriorating service and the descriptions of specific impairments, for example, are needed for rapid corrective actions. This paper describes both common industry approaches to quality monitoring for Hypertext Transfer Protocol (HTTP) Live Streaming (HLS) and dynamic adaptive streaming over HTTP (DASH) delivery methods as well as video content quality evaluation leveraging mean opinion score (MOS), bits per pixel, and other metrics aimed at evaluating if viewers have a satisfactory viewing experience. A comprehensive set of metrics including both those recommended by standards and trade groups as well as key supplemental metrics for both end user viewing and transport system analysis is discussed along with the tradeoffs in measurement implementation techniques gained from significant deployments for some past entertainment events. Recommendations on the selection of a mix of reactive and proactive metrics are provided as derived from synthetic clients, passive agent technologies, and virtual swarming agents. Both transport and content quality metrics are critical in assessing viewers’ experience and pinpointing impairment causes and viewer losses.
机译:随着用于视频传输交付的自适应比特率技术的日益复杂,质量保证复杂性也相应增加。视频服务提供商需要更多的信息,而不仅仅是一些观众对其观看体验感到不满意。例如,需要采取更积极主动的警告,告知服务质量不断下降,并描述特定的损坏,以采取迅速的纠正措施。本文介绍了针对超文本传输​​协议(HTTP)实时流(HLS)和基于HTTP的动态自适应流(DASH)交付方法进行质量监控的常见行业方法,以及利用平均意见得分(MOS),每位位数的视频内容质量评估像素以及旨在评估观看者是否有令人满意的观看体验的其他指标。讨论了一组全面的度量标准,包括标准和贸易组推荐的度量标准,以及用于最终用户查看和传输系统分析的关键补充度量标准,以及从过去一些娱乐活动的大量部署中获得的度量实施技术的权衡。提供了从混合客户端,被动代理技术和虚拟集群代理派生而来的关于选择反应性和主动性指标混合的建议。传输质量指标和内容质量指标对于评估观众的体验并查明损害原因和观众损失至关重要。

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