A Sub-Partitioning Method for Point Cloud Inter-prediction Coding

In recent years, 3D point clouds have gained more attention with the possibility of applications such as virtual reality, autonomous vehicles and 3D mapping of historical artifacts, among others. However, raw point clouds generate very large amounts of data. Thus, compression is essential to enable emerging 3D systems for communication and storage.This paper presents an inter prediction technique based on the ICP algorithm and variable-size macroblocks that can be used to significantly reduce the number of bits required to represent a point cloud video sequence by inter coding the geometry information. Since consecutive frames in dynamic point cloud sequences are not guaranteed to fill the exact same 3D volume, a spatial alignment step before motion estimation is required to increase the likelihood of good matchings and thus generate a high number of inter-coded macroblocks. A decision step is also included in order to select the most favorable coding mode: intra-coding, inter-coding or inter-coding with macroblock subdivision. The proposed technique was tested in the PCC MPEG reference software and four MPEG test sequences, obtaining average bitrate reductions of about 8% with PSNR gains up to 1dB.