@inproceedings{bfd1a33807444ebeb7b9e9e76f9d9a98,
title = "Scene Graph Driven Hybrid Interactive VR Teleconferencing",
abstract = "We propose an interactive and intelligent hybrid teleconferencing system compatible with Virtual Reality devices. Our system understands meeting contexts and leverages user interactions to enhance better system configuration. Employing interactive scene graphs [11], the system extracts and transmits essential meeting context to users while relaying user interactions back to the streaming systems for user-involved adaptive streaming and foveated rendering. We demonstrate the system's real-time performance and compatibility with commercial VR devices such as the Meta Quest 3.",
keywords = "machine learning, teleconferencing system, virtual reality",
author = "Mingyuan Wu and Ruifan Ji and Haozhen Zheng and Jiaxi Li and Beitong Tian and Bo Chen and Ruixiao Zhang and Jacob Chakareski and Michael Zink and Ramesh Sitaraman and Klara Nahrstedt",
note = "Thi swork was supported by the National Science Foundation grants NSF CNS 19-00875, NSF CNS 21-06592, NSF OAC 18-35834 KN, NSF CCF 22-17144, NSF CNS-1901137, and NSF CNS-2106463. Jacob Chakareski has been supported in part by NSF CCF-2031881, NSF ECCS-2032387, NSF CNS-2040088, NSF CNS-2032033, and NSF CNS-2106150; NIH R01EY030470; and by the Panasonic Chair of Sustainability at the New Jersey Institute for Technology. Any results and opinions are our own and do not represent views of National Science Foundation.; 32nd ACM International Conference on Multimedia, MM 2024 ; Conference date: 28-10-2024 Through 01-11-2024",
year = "2024",
month = oct,
day = "28",
doi = "10.1145/3664647.3684996",
language = "English (US)",
series = "MM 2024 - Proceedings of the 32nd ACM International Conference on Multimedia",
publisher = "Association for Computing Machinery",
pages = "11276--11278",
booktitle = "MM 2024 - Proceedings of the 32nd ACM International Conference on Multimedia",
address = "United States",
}