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ACM MM2023顶会

Hermes: Leveraging Implicit Inter-Frame Correlation for Bandwidth-Efficient Mobile Volumetric Video Streaming

Yizong Wang, Dong Zhao, Huanhuan Zhang, Chenghao Huang, Teng Gao, Zixuan Guo, Liming Pang, Huadong Ma

2023年份
13被引次数
1顶会引用

摘要

Volumetric videos offer viewers more immersive experiences, enabling a variety of applications. However, state-of-the-art streaming systems still need hundreds of Mbps, exceeding the common bandwidth capabilities of mobile devices. We find a research gap in reusing inter-frame redundant information to reduce bandwidth consumption, while the existing inter-frame compression methods rely on the so-called explicit correlation, i.e., the redundancy from the same/adjacent locations in the previous frame, which does not apply to highly dynamic frames or dynamic viewports. This work introduces a new concept called implicit correlation, i.e., the consistency of topological structures, which stably exists in dynamic frames and is beneficial for reducing bandwidth consumption. We design a mobile volumetric video streaming system Hermes consisting of an implicit correlation encoder to reduce bandwidth consumption and a hybrid streaming method that adapts to dynamic viewports. Experiments show that Hermes achieves a frame rate of 30+ FPS over daily networks and on commodity smartphones, with at least 3.37x improvement compared with two baselines.

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