Distortion Propagation Model-Based V-PCC Rate Control for 3D Point Cloud Broadcasting
Zhanyuan Cai, Wenxu Gao, Ge Li, Wei Gao
Abstract
For efficient point cloud broadcasting, point cloud compression technologies serve as the foundation, which plays a crucial role in immersive media communication and streaming. Video-based point cloud compression (V-PCC) is the recently developed standard by the Moving Picture Experts Group (MPEG) for dynamic point clouds. Its original fixed-ratio bit allocation (FR-BA) method in the unique all intra (AI) structure leads to a significant rate-distortion performance gap between the rate control manner and the fixed quantization parameters (FixedQP) scheme, as evidenced by significant increases in BD-Rate (Bjøntegaard Delta Rate) for both geometry and attribute. To address this issue, we propose a distortion propagation model-based frame-level bit allocation method that is specifically tailored for AI structure in V-PCC. First, the analysis is carried out for the distortion propagation model inside the group of pictures (GOP) for the AI configuration. Second, the skip ratio of 4x4 minimum coding units (CUs) is utilized to predict the distortion propagation factor. Third, the occupancy information is employed to refine the distortion propagation model and further enhance compression performance. Finally, experimental results demonstrate the effectiveness of the proposed distortion propagation model-based frame-level bit allocation method. Specifically, experimental results reveal that the proposed method achieves BD-Rate reductions of 0.92% and 4.85% in geometry and attribute, respectively, compared to the FR-BA method. Furthermore, with the introduction of distortion propagation factor prediction incorporating occupancy correction, the BD-Rate reductions are further extended to 2.16% and 6.13% in geometry and attribute, respectively.