Point cloud compression on the basis 3D motion estimation and compensation

Abstract

The point cloud is a medium that visualizes various information by placing a point having a color value and a geometry value in a three-dimensional space. The point cloud uses dozens and millions of points for visualization of information, and the key point of commercialization of this point cloud video is to efficiently compress a large amount of information of point cloud and transmit it to users. Currently, MPEG V-PCC is conducting dynamic point cloud compression research using the 2D video codec, where motion estimation is conducted in terms of 2D video sequences. Thus, there is a limitation in estimating the motion in 3D point cloud contents. In this paper, we propose the method to use the 3D motion for point cloud video compression. The proposed technology achieves efficient compression rate and improves accuracy in lossy compression.