Vues: Practical Mobile Volumetric Video Streaming Through Multiview Transcoding
Vues: Practical Mobile Volumetric Video Streaming Through Multiview Transcoding
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Vues：通过多视图转码实现实用的移动体积视频流
DOI：
10.1145/3495243.3517027
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发表时间：
2022
期刊：
影响因子：
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通讯作者：
Zhang, Zhi-Li
中科院分区：
文献类型：
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作者：
Liu, Yu;Han, Bo;Qian, Feng;Narayanan, Arvind;Zhang, Zhi-Li
新兴的体积视频提供了完全身临其境的六自由度(6DoF)观看体验，但代价是极高的带宽需求。在本文中，我们设计、实现并评估了一个边缘辅助转码系统VUE，它可以在移动设备上提供低带宽要求、低解码开销和高质量体验的高质量体积视频。通过IRB批准的用户研究，我们构建了首个此类QOE模型，以量化通过将体积内容代码转换为2D视频而引入的各种因素的影响。在这项用户研究的关键观察结果的激励下，VUE采用了一种新颖的多视角方法，总体目标是提高QOE。VUE边缘服务器在几个轻量级机器学习模型的帮助下，自适应地将一个体积视频帧转码为多个2D视图，并战略性地平衡额外视图的额外带宽消耗和改进的QOE，如我们的QOE模型所示。客户端在所传递的候选对象中选择优化QOE的视图以供显示。使用原型实施进行的综合评估表明，VUE的性能大大优于现有方法。平均而言，与单视图转码方案相比，它的QOE提高了35%(高达85%)，与最先进的直接流式传输体积视频的方案相比，带宽消耗降低了95%。
The emerging volumetric videos offer a fully immersive, six degrees of freedom (6DoF) viewing experience, at the cost of extremely high bandwidth demand. In this paper, we design, implement, and evaluate Vues, an edge-assisted transcoding system that delivers high-quality volumetric videos withlow bandwidth requirement, low decoding overhead, andhigh quality of experience (QoE)on mobile devices. Through an IRB-approved user study, we build a first-of-its-kind QoE model to quantify the impact of various factors introduced by transcoding volumetric content into 2D videos. Motivated by the key observations from this user study, Vues employs a novelmultiviewapproach with the overarching goal of boosting QoE. The Vues edge server adaptively transcodes a volumetric video frame into multiple 2D views with the help of a few lightweight machine learning models and strategically balances the extra bandwidth consumption of additional views and the improved QoE, indicated by our QoE model. The client selects the view that optimizes the QoE among the delivered candidates for display. Comprehensive evaluations using a prototype implementation indicate that Vues dramatically outperforms existing approaches. On average, it improves the QoE by 35% (up to 85%), compared to single-view transcoding schemes, and reduces the bandwidth consumption by 95%, compared to the state-of-the-art that directly streams volumetric videos.