迈向高效的多编解码器流

Y. Reznik, K. Lillevold, Abhijith Jagannath, Nabajeet Barman
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引用次数: 2

摘要

现代流媒体最大的挑战之一是接收设备对编解码器支持的碎片化。例如,现代苹果设备可以解码并在H.264/AVC和HEVC流之间无缝切换。大多数新电视和机顶盒也可以解码HEVC,但它们不能在HEVC和H.264/AVC流之间切换。还有很多旧设备/流媒体客户端只能接收和解码H.264/AVC流。随着下一代编解码器(如AV1和VVC)的到来,跨设备的编解码器支持的碎片化变得更加复杂。这种情况带来了一个问题——我们如何通过使用编解码器在所有情况下提供最佳性能,同时产生尽可能少的流,从而最有效地服务于如此多的设备,从而使媒体传输的总成本最小?在本文中,我们解释了如何在ABR流的编码配置文件动态生成阶段形式化和解决这个问题。提出的解决方案是上下文感知编码(CAE)类技术的泛化,考虑了使用每个编解码器生成的多组场景和接收设备的编解码器使用分布。我们还讨论了使所建议的解决方案实际可部署所需的几个流系统级工具。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Towards efficient multi-codec streaming
One of the biggest challenges in modern-era streaming is the fragmentation of codec support across receiving devices. For example, modern Apple devices can decode and seamlessly switch between H.264/AVC and HEVC streams. Most new TVs and set-top boxes can also decode HEVC, but they cannot switch between HEVC and H.264/AVC streams. And there are still plenty of older devices/streaming clients that can only receive and decode H.264/AVC streams. With the arrival of next-generation codecs - such as AV1 and VVC, the fragmentation of codec support across devices becomes even more complex. This situation brings a question – how we can serve such a population of devices most efficiently by using codecs delivering the best performance in all cases yet producing the minimum possible number of streams and such that the overall cost of media delivery is minimal? In this paper, we explain how this problem can be formalized and solved at the stage of dynamic generation of encoding profiles for ABR streaming. The proposed solution is a generalization of context-aware encoding (CAE) class-of techniques, considering multiple sets of renditions generated using each codec and codec usage distributions by the population of the receiving devices. We also discuss several streaming system-level tools needed to make the proposed solution practically deployable.
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