Title: Point Cloud Streaming with Latency-Driven Implicit Adaptation using MoQ Show Chinese title

Title: 基于MoQ的延迟驱动隐式自适应点云流

Abstract: Point clouds are a promising video representation for next-generation multimedia experiences in virtual and augmented reality. Point clouds are notoriously high-bitrate, however, which limits the feasibility of live streaming systems. Prior methods have adopted traditional HTTP-based protocols for point cloud streaming, but they rely on explicit client-side adaptation to maintain low latency under congestion. 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. Show Chinese abstract

Abstract: 点云是虚拟和增强现实中下一代多媒体体验的一种有前景的视频表示形式。 点云的比特率却众所周知很高，这限制了实时流媒体系统的可行性。 之前的方法采用了基于传统HTTP的协议进行点云流传输，但它们依赖于客户端的显式适应以在拥塞情况下保持低延迟。 在本工作中，我们利用Media Over QUIC协议中的传输超时功能，根据应用程序的延迟目标执行隐式的服务器端适应。 通过在多个发布者和网络配置下的实验，我们证明了我们的系统在每个客户端的基础上实现了独特的权衡：延迟要求较低的应用将获得较低质量的视频，而延迟要求较宽松的应用将获得较高质量的视频。