Dynamic point cloud (DPC) captures 3D object and scene with realistic appearance to mimic the natural reality. It inherently offers the six-degree-of-freedom (6DoF) for content consumption, which motivates us to facilitate the network-friendly view-dependent DPC streaming by leveraging the limited field of view of the human visual system (HVS) at specific moments, for significant network bandwidth reduction without the quality of experience (QoE) loss. Therefore, in this work, we propose the view-dependent DPC compression, noted as View-PCC, by which we can enable instantaneous and complete view reconstruction from partial streams, and 6DoF navigation by stream adaptation. These functionalities are offered by the hybrid global and local projection to effectively map 3D points to five perpendicular 2D image planes of a cube. Multi-view and multi-layer based global projection is first applied progressively and followed by the patch-based local projection with both intra-frame displaced arrangement and inter-frame temporal alignment, so as to maximize the number of effectively projected points and preserve the spatio-temporal coherency for better compression. Boundary padding is then augmented for each image plane that will be encoded using the successful 2D video coding standard -High-Efficiency Video Coding (HEVC). Our extensive simulations have shown the noticeable objective compression gains of View-PCC when compared with the typical octree-based approach and global-projection-based method. The subjective quality assessment suggests the better reconstruction quality of View-PCC, in comparison to the MPEG video-based point cloud compression (V-PCC).

中文翻译：

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视点相关的动态点云压缩

动态点云 (DPC) 捕捉具有逼真外观的 3D 对象和场景，以模仿自然现实。它本质上为内容消费提供了六自由度 (6DoF)，这促使我们通过在特定时刻利用人类视觉系统 (HVS) 的有限视野来促进网络友好的依赖于视图的 DPC 流，在不损失体验质量 (QoE) 的情况下显着减少网络带宽。因此，在这项工作中，我们提出了依赖于视图的 DPC 压缩，称为 View-PCC，通过它我们可以从部分流中实现即时和完整的视图重建，以及通过流自适应进行 6DoF 导航。这些功能由混合全局和局部投影提供，可有效地将 3D 点映射到立方体的五个垂直 2D 图像平面。多视角和多层的全局投影首先逐步应用，然后是基于块的局部投影，同时具有帧内位移排列和帧间时间对齐，以最大化有效投影点的数量并保留时空一致性以实现更好的压缩。然后为每个将使用成功的 2D 视频编码标准 - 高效视频编码 (HEVC) 进行编码的图像平面增加边界填充。我们广泛的模拟表明，与典型的基于八叉树的方法和基于全局投影的方法相比，View-PCC 具有明显的客观压缩增益。与基于 MPEG 视频的点云压缩 (V-PCC) 相比，主观质量评估表明 View-PCC 的重建质量更好。