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Advancing User Quality of Experience Using Viewport Archives in Viewport-Aware Tile-Based 360-Degree Video Streaming

机译:使用视口归档在基于视口的360度视频流中使用视口归档的用户质量推进体验

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In tile-based 360-degree video streaming, the video content is temporally divided into segments, wherein the content is further divided spatially into multiple partitions called tiles. As a common technique to reduce the data size for the segment in tile-based streaming, various viewport prediction models are adopted to allocate bandwidth to the tiles within the region predicted for the user, which is also called the quality enhanced region or viewport. However, due to the unpredictable nature of user head movements, it is difficult to accurately estimate the viewport, resulting in great degradation in the Quality of Experience (QoE) for the user. In this paper, to improve user QoE for even when there are estimation errors, we propose extending the viewport to include the direction(s) holding the highest likelihood to be seen by the user by assigning weights to each tile of each segment from the viewport archives of past users. From our performance evaluation on two 360-degree videos, the proposed method demonstrated a significant increase in the perceived viewport quality while suppressing quality variation within the viewport and across segments compared to two reference models.
机译:在基于图块的360度视频流中,视频内容在时间上被划分为段,其中内容进一步将空间划分为称为瓦片的多个分区。作为减少基于图块的流的段的段的数据大小的常用技术,采用各种视口预测模型将带宽分配给用户内预测的区域内的瓦片,这也称为质量增强区域或视口。然而,由于用户头部运动的不可预测性,很难准确估计视口,导致用户的经验质量(QoE)劣化。在本文中,为了改善用户QoE,即使存在估计错误,也提出扩展视口以包括通过将权重从视口分配给每个段的每个段的每个磁座来包括用户所看到的最高可能性的方向过去的用户档案。从我们在两个360度视频上进行性能评估,所提出的方法在与两个参考模型相比,抑制了视口内的质量变化,并且抑制了视口内的质量变化,并且与两个参考模型相比,抑制了视口内的质量变化的显着增加。

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