A Networking Perspective of Volumetric Video Service: Architecture, Opportunities, and Case Study

Recent years have witnessed the prompt development of multimedia applications over the Internet, where volumetric video stands out as a thrilling new video paradigm, leading a revolution from traditional flat 2D to the future volumetric 3D experience with spatialized immersion and 6 degree-of-freedom interactivity. It serves as a key technical foundation of AR, VR, MR, and the emerging Metaverse. In this paper, we mainly study the volumetric video service from a networking perspective. We start with a comprehensive overview of the volumetric video, clarifying its evolution and unique features. We then present a holistic view of the architecture of volumetric video service from a networking perspective, including video capture, representation, streaming, and display. Research opportunities and challenges are next discussed. Finally, we present our design on volumetric video streaming as a case study. The proposed framework achieves accurate 6 DoF viewport prediction while employing deep reinforcement learning for adaptive streaming. The evaluation demonstrates its effectiveness, exhibiting a nearly 30% improvement compared to existing systems.

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Publication Details

Journal
IEEE Network
Published
2024-08-12
DOI
https://doi.org/10.1109/mnet.2024.3442210
Citations
8
Primary Topic
Caching and Content Delivery
Type
article
Field-Weighted Citation Impact
2.79
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article

A Networking Perspective of Volumetric Video Service: Architecture, Opportunities, and Case Study

Kaiyuan Hu, Yili Jin, Junhua Liu, Fangxin Wang
8 citations
IEEE Network
Caching and Content Delivery
2.79
article

A Networking Perspective of Volumetric Video Service: Architecture, Opportunities, and Case Study

Kaiyuan Hu, Yili Jin, Junhua Liu, Fangxin Wang
article en
8 citations

Abstract

Recent years have witnessed the prompt development of multimedia applications over the Internet, where volumetric video stands out as a thrilling new video paradigm, leading a revolution from traditional flat 2D to the future volumetric 3D experience with spatialized immersion and 6 degree-of-freedom interactivity. It serves as a key technical foundation of AR, VR, MR, and the emerging Metaverse. In this paper, we mainly study the volumetric video service from a networking perspective. We start with a comprehensive overview of the volumetric video, clarifying its evolution and unique features. We then present a holistic view of the architecture of volumetric video service from a networking perspective, including video capture, representation, streaming, and display. Research opportunities and challenges are next discussed. Finally, we present our design on volumetric video streaming as a case study. The proposed framework achieves accurate 6 DoF viewport prediction while employing deep reinforcement learning for adaptive streaming. The evaluation demonstrates its effectiveness, exhibiting a nearly 30% improvement compared to existing systems.

IEEE NetworkVol. 38(6)
Chinese University of Hong Kong, Shenzhen (CN)
Sustainable cities and communities
Openalex Percentile: Top 9%
Caching and Content Delivery
2.79
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