Point cloud video is the most popular representation of hologram, which is the medium to precedent natural content in VR/AR/MR and is expected to be the next generation video. Point cloud video system provides users immersive viewing experience with six degrees of freedom and has wide applications in many fields such as online education, entertainment. To further enhance these applications, point cloud video streaming is in critical demand. The inherent challenges lie in the large size by the necessity of recording the three-dimensional coordinates besides color information, and the associated high computation complexity of encoding. To this end, this paper proposes a communication and computation resource allocation scheme for QoE-driven point cloud video streaming. In particular, we maximize system resource utilization by selecting different quantities, transmission forms and quality level tiles to maximize the quality of experience. Extensive simulations are conducted and the simulation results show the superior performance over the existing schemes

中文翻译：

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QoE驱动的点云视频流的联合通信和计算资源分配

点云视频是全息图最流行的表示形式，它是 VR/AR/MR 中自然内容的先例，有望成为下一代视频。点云视频系统为用户提供六自由度的沉浸式观看体验，在在线教育、娱乐等诸多领域有着广泛的应用。为了进一步增强这些应用程序，点云视频流的需求非常迫切。固有的挑战在于需要记录除颜色信息之外的 3 维坐标而导致的大尺寸，以及相关的高计算复杂度的编码。为此，本文提出了一种QoE驱动的点云视频流的通信和计算资源分配方案。特别是，我们通过选择不同数量、传输形式和质量级别的瓦片来最大限度地提高系统资源利用率，以最大限度地提高体验质量。进行了广泛的模拟，模拟结果表明优于现有方案的性能