Navigation Graph for Tiled Media Streaming
Navigation Graph for Tiled Media Streaming
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DOI：
10.1145/3343031.3351021
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发表时间：
2019-10
期刊：
影响因子：
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通讯作者：
Jounsup Park;K. Nahrstedt
中科院分区：
文献类型：
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作者：
Jounsup Park;K. Nahrstedt
视频流服务出现后，更多创意和多样化的多媒体内容出现，现在360度视频流的能力将开启多媒体体验的新时代。然而，与传统视频流系统相比，流式传输这些视频需要更大的带宽和更少的延迟。平铺视频的速率自适应和视图预测技术用于解决这个问题。在本文中，我们介绍了导航图，它对时间（片段）和空间（图块）域中的观看行为进行建模，以执行与视图预测相关的图块媒体的速率自适应。导航图允许客户端通过共享观看模型来更轻松地执行观看预测，就像在 DASH 中共享媒体描述信息一样。它对于在媒体描述文件中编码轨迹信息也很有用，这也可以实现更有效的 360 度视频导航。本文提供了有关导航图的创建及其用途的信息。性能评估表明，基于导航图的视图预测和速率自适应优于其他现有的平铺媒体流解决方案。 Navigation Graph 不仅限于 360 度视频流应用，还可以应用于其他平铺媒体流系统，例如用于增强现实应用的体积媒体流。
After the emergence of video streaming services, more creative and diverse multimedia content has become available, and now the capability of streaming 360-degree videos will open a new era of multimedia experiences. However, streaming these videos requires larger bandwidth and less latency than what is found in conventional video streaming systems. Rate adaptation of tiled videos and view prediction techniques are used to solve this problem. In this paper, we introduce the Navigation Graph, which models viewing behaviors in the temporal (segments) and the spatial (tiles) domains to perform the rate adaptation of tiled media associated with the view prediction. The Navigation Graph allows clients to perform view prediction more easily by sharing the viewing model in the same way in which media description information is shared in DASH. It is also useful for encoding the trajectory information in the media description file, which could also allow for more efficient navigation of 360-degree videos. This paper provides information about the creation of the Navigation Graph and its uses. The performance evaluation shows that the Navigation Graph based view prediction and rate adaptation outperform other existing tiled media streaming solutions. Navigation Graph is not limited to 360-degree video streaming applications, but it can also be applied to other tiled media streaming systems, such as volumetric media streaming for augmented reality applications.