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.
Authors
- Kaiyuan Hu (ORCID: https://orcid.org/0009-0003-2709-457X)
- Yili Jin (ORCID: https://orcid.org/0000-0002-7127-8902)
- Junhua Liu (ORCID: https://orcid.org/0009-0007-4494-765X)
- Fangxin Wang (ORCID: https://orcid.org/0000-0003-2559-045X)
Institutions
- Chinese University of Hong Kong, Shenzhen (CN)
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