面向全息视频通信的自适应分块传输方法
Towards Holographic Video Communications:An Adaptive Tiling Solution
朱原玮 1黄亚坤 1乔秀全1
作者信息
- 1. 北京邮电大学网络与交换技术全国重点实验室,北京 100876
- 折叠
摘要
基于分治和按需传输思想的分块传输技术是解决三维全息视频流传输的有效手段.然而,现有的分块方案要么缺乏自适应机制,要么不适用于移动实时通信场景.为此,本文提出了VVSTiler(Volumetric Video Streaming Tiling selector),一种面向全息视频通信的自适应分块传输方法,能够在动态且有限的计算和带宽资源下最大化视频的观感质量.具体而言,本文对不同粒度的分块方案带来的影响进行了初步研究,发现细粒度的分块方案可提高动态网络资源的利用率,粗粒度的分块方案可保证视频编解码效率和鲁棒性.基于此,本文构建了考虑预测视口、可用计算资源以及网络带宽等上下文信息的视频观感质量优化问题,并设计了一个高效的求解方案以支持在线的分块粒度决策.本文在8iVFB(8i Voxelized Full Bodies)标准数据集上将VVSTiler与当前主流的分块传输方法进行了比较.实验结果表明,VVSTiler在有偏差的视口预测情况下实现了高达60.4％的视频观感质量提升,在较准确的视口预测情况下平均每帧视频节省了27％的带宽资源.
Abstract
Tile-based methods that use the divide-and-conquer and on-demand transmission techniques are promising to handle 3D holographic video streaming.However,the current solutions either lack an adaptive tiling scheme or cannot apply to mobile real-time scenarios.In this paper,we propose VVSTiler(Volumetric Video Streaming Tiling selector),an adaptive tiling selector for holographic video communications,which can adaptively maximize perceived video quality un-der dynamic and limited computing and bandwidth resources.To be specific,we first conduct a preliminary study on the impacts of different tiling schemes and find that fine-grained tiles improve the rational utilization of dynamic network re-sources and coarse tiles ensure coding efficiency and robustness,which stimulates us to construct an adaptive tiling optimi-zation based on the predicted viewport,available computing resources,and network bandwidth;and then devise a fast algo-rithm to enable online tiling decisions.Rich experiments on the 8iVFB(8i Voxelized Full Bodies)datasets are conducted to compare VVSTiler with state-of-the-art tiling-based baselines.The results exhibit that VVSTiler can achieve up to 60.4％video quality improvements and save on average 27％bandwidth per frame against the closest competitor,in cases of terri-ble and accurate viewport predictions,respectively.
关键词
全息视频通信/体积视频流/点云视频/自适应分块/视口预测/视频观感质量Key words
holographic video communications/volumetric video streaming/point cloud video/adaptive tiling/viewport prediction/perceived video quality引用本文复制引用
基金项目
国家重点研发计划(2022YFB2902900)
国家自然科学基金(62202065)
出版年
2024
国家科技期刊平台
NSTL
万方数据