Point Cloud Streaming with Latency-Driven Implicit Adaptation using MoQ
Andrew Freeman, Michael Rudolph, Amr Rizk

TL;DR
This paper introduces a latency-driven implicit adaptation method for point cloud streaming over QUIC, optimizing video quality based on individual application's latency needs, thereby improving streaming efficiency for virtual and augmented reality.
Contribution
It presents a novel server-side adaptation technique leveraging QUIC's delivery timeout to dynamically adjust point cloud quality according to latency targets.
Findings
Lower latency applications receive lower-quality point clouds
Higher latency applications receive higher-quality point clouds
System demonstrates effective latency-quality trade-offs
Abstract
Point clouds are a promising video representation for virtual and augmented reality. Their high-bitrate, however, has so far limited the practicality of live streaming systems. In this work, we leverage the delivery timeout feature within the Media Over QUIC protocol to perform implicit server-side adaptation based on an application's latency target. Through experimentation with several publisher and network configurations, we demonstrate that our system unlocks a unique trade-off on a per-client basis: applications with lower latency requirements will receive lower-quality video, while applications with more relaxed latency requirements will receive higher-quality video.
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Taxonomy
TopicsVirtual Reality Applications and Impacts · IoT and Edge/Fog Computing · 3D Shape Modeling and Analysis
