LiVo: Toward Bandwidth-adaptive Fully-Immersive Volumetric Video Conferencing
Volumetric video allows users 6 degrees of freedom (6-DoF) in viewing continuously evolving scenes in 3D. Given broadband speeds today, volumetric video conferencing will soon be feasible. Even so, these scenes will need to be compressed, and compression will need to adapt to variations in bandwidth availability. Existing 3D compression techniques cannot adapt to bandwidth availability, are slow, and utilize bandwidth inefficiently, so they don't scale well to large scene descriptions. LiVo achieves low-latency and large-scene two-way conferencing by maximally leveraging existing 2D video infrastructure, including compression standards, rate-adaptive codecs, and real-time transport protocols. To achieve high quality, LiVo must carefully compose scenes from multiple cameras into multiple streams, encode scene geometry in a novel way, adapt to and apportion available bandwidth dynamically between streams to ensure high reconstruction quality, and cull content outside the receiver's field of view to reduce information sent into the network. These novel contributions enable LiVo to outperform the state-of-the-art by over 20% in objective quality. In a user study, LiVo achieves a mean opinion score of 4.1, while other approaches achieve significantly lower values.
Authors
- Muyang Ye (ORCID: https://orcid.org/0009-0007-9527-0431)
- Tao Jin (ORCID: https://orcid.org/0000-0001-5018-3958)
- Antonio Ortega (ORCID: https://orcid.org/0000-0001-5403-0940)
- Ramesh Govindan
- Rajrup Ghosh (ORCID: https://orcid.org/0000-0002-9797-2417)
- Christina Suyong Shin (ORCID: https://orcid.org/0000-0001-5653-5571)
- Ravi Netravali (ORCID: https://orcid.org/0000-0001-7002-5033)
- Anthony Rowe (ORCID: https://orcid.org/0000-0003-2332-9450)
- Sanjay Rao (ORCID: https://orcid.org/0000-0003-4825-4352)
- Harsha V. Madhyastha (ORCID: https://orcid.org/0009-0000-3921-5680)
- Lei Zhang (ORCID: https://orcid.org/0009-0002-5132-4251)
Institutions
- University of Southern California (US)
- Bellevue College (US)
- Princeton University (US)
- Purdue University West Lafayette (US)
- Bellevue University (US)
- Carnegie Mellon University (US)
Publication Details
- Journal
- Proceedings of the ACM on Networking
- Published
- 2025-11-24
- DOI
- https://doi.org/10.1145/3768981
- Primary Topic
- Video Coding and Compression Technologies
- Type
- article
- Field-Weighted Citation Impact
- 0.00