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Demo: Horizon: a Real-time Point Cloud Video Streaming System over Wireless Networks

Published: 18 June 2023 Publication History

Abstract

As a popular way of representing holographic video or volumetric video, point cloud video can provide users with a highly immersive viewing experience of 6 degrees of freedom (6DoF) and is expected to become the mainstream video format of the future. However, the real-time transmission of point cloud video faces many challenges due to the huge amount of data and the large search space of the optimization problem with constraints. To this end, we propose Horizon, a novel Dynamic Adaptive Streaming over HTTP (DASH) based real-time point cloud video streaming system, which aims to maximize the user's viewing experience by predicting the next several steps through a rolling framework and uses a Deep Reinforcement Learning (DRL) based algorithm to achieve a real-time solution to the rolling optimization problem. We have prototyped this system and demonstrated its performance on a state-of-the-art wireless network.

References

[1]
Eugene d'Eon, Bob Harrison, Taos Myers, and Philip A Chou. 2017. 8i voxelized full bodies-a voxelized point cloud dataset. ISO/IEC JTC1/SC29 Joint WG11/WG1 (MPEG/JPEG) input document WG11M40059/WG1M74006 7, 8 (2017), 11.
[2]
Jie Li, Cong Zhang, Zhi Liu, Richang Hong, and Han Hu. 2022. Optimal Volumetric Video Streaming with Hybrid Saliency based Tiling. IEEE Transactions on Multimedia (2022), 1--1.
[3]
Zhi Liu, Qiyue Li, Xianfu Chen, Celimuge Wu, Susumu Ishihara, Jie Li, and Yusheng Ji. 2021. Point Cloud Video Streaming: Challenges and Solutions. IEEE Network 35, 5 (2021), 202--209.
[4]
Li Yu, Tammam Tillo, and Jimin Xiao. 2017. QoE-Driven Dynamic Adaptive Video Streaming Strategy With Future Information. IEEE Transactions on Broadcasting 63, 3 (2017), 523--534.

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  1. Demo: Horizon: a Real-time Point Cloud Video Streaming System over Wireless Networks

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    cover image ACM Conferences
    MobiSys '23: Proceedings of the 21st Annual International Conference on Mobile Systems, Applications and Services
    June 2023
    651 pages
    ISBN:9798400701108
    DOI:10.1145/3581791
    Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the owner/author(s).

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    Publication History

    Published: 18 June 2023

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    Author Tags

    1. point cloud
    2. video streaming
    3. DASH
    4. rolling optimization
    5. reinforcement learning

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    MobiSys '23 Paper Acceptance Rate 41 of 198 submissions, 21%;
    Overall Acceptance Rate 274 of 1,679 submissions, 16%

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