G-PCC Point Cloud Transmission with Temporal Track Separation

The patent segments point cloud data into multiple layers based on depth distance, creating a hierarchical structure where points are organized into near, mid, and far layers. This segmentation enables parallel processing of different layers and reduces the computational complexity of handling all points simultaneously, thereby improving processing efficiency and reducing latency.

The patent introduces a depth-based dimensional organization by sorting points according to their distance from the camera and arranging them in multiple layers along the depth axis. This dimensional transformation from a uniform point set to a layered spatial structure enables more efficient memory access patterns and reduces processing latency.

The patent divides the point cloud into multiple layers based on depth, allowing different processing strategies to be applied to each layer. This segmentation maintains processing accuracy for near points while using coarser representations for far points, thereby reducing overall encoding/decoding complexity without sacrificing critical detail.

The patent applies different processing qualities to different spatial regions by organizing points into layers where near layers (containing more detailed information) are processed with higher fidelity and far layers are processed with reduced complexity. This local quality approach maintains accuracy where needed while reducing complexity in less critical regions.