Abstract
Virtual reality (VR) holds a great potential to provide interactive and immersive learning experiences for students in remote education by using existing mobile devices, which is extremely meaningful during the current pandemic. In such a VR application, satisfactory user experience requires: 1) high-resolution panoramic image rendering; 2) high frame rate; 3) synchronization among users. This requires that either mobile devices perform fast image rendering or today's wireless network can support multi-Gbps traffic with extremely low delay, neither of which is the case in current practice. In this demo, we develop a platform for interactive and immersive remote education based on commodity devices, where a server performs rendering to ensure that the rendered images have high-resolution (2560×1440 pixels) and are displayed at a high frame rate (60 frames per second) on the client-side. We further leverage motion prediction to overcome the diverse round-trip time (RTT) between a server and users and ensure synchronization among users (average 9.2 ms frame latency difference among users), which improves at least 60% and 20% compared to the existing local-rendering and server-rendering methods, respectively.
Original language | English (US) |
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Title of host publication | IEEE INFOCOM 2021 - IEEE Conference on Computer Communications Workshops, INFOCOM WKSHPS 2021 |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
ISBN (Electronic) | 9781665404433 |
DOIs | |
State | Published - May 10 2021 |
Event | 2021 IEEE Conference on Computer Communications Workshops, INFOCOM WKSHPS 2021 - Virtual, Online Duration: May 9 2021 → May 12 2021 |
Publication series
Name | IEEE INFOCOM 2021 - IEEE Conference on Computer Communications Workshops, INFOCOM WKSHPS 2021 |
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Conference
Conference | 2021 IEEE Conference on Computer Communications Workshops, INFOCOM WKSHPS 2021 |
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City | Virtual, Online |
Period | 5/9/21 → 5/12/21 |
Bibliographical note
Funding Information:This research has been supported in part by NSF grants: CNS-1717108, CNS-1815563, CNS-1942383, and CNS-1915122.
Publisher Copyright:
© 2021 IEEE.