DYNAMIC POINT CLOUD COMPRESSION APPROACH USING HEXAHEDRON SEGMENTATION

Video-based point cloud compression (V-PCC) is the state-of-the-art standard for compressing dynamic point clouds, a newly developed media format. However, real-time V-PCC applications are challenging because of excessive encoding complexity. This approach relies on converting 3D data into 2D frames using patch generation and refinement processes, which is one of the most computationally demanding components of V-PCC. This paper proposes a suitable-sized hexahedron and its projection plane by investigating different sizes of regular hexahedron partitioning and projection planes to convert 3D data to 2D without needing the complex patch generation and refinement processes while preserving more data and accuracy. The experimental results demonstrate that the chosen hexahedron can reduce the patch generation time of the V-PCC significantly. The proposed technique also minimises the point cloud losses, thus improving the image quality, and requires a smaller size of 2D maps than the V-PCC to further reduce the required bits for compression.