Refining the bounding volumes for lossless compression of voxelized point clouds geometry

This paper describes a novel lossless compression method for point cloud\ngeometry, building on a recent lossy compression method that aimed at\nreconstructing only the bounding volume of a point cloud. The proposed scheme\nstarts by partially reconstructing the geometry from the two depthmaps\nassociated to a single projection direction. The partial reconstruction\nobtained from the depthmaps is completed to a full reconstruction of the point\ncloud by sweeping section by section along one direction and encoding the\npoints which were not contained in the two depthmaps. The main ingredient is a\nlist-based encoding of the inner points (situated inside the feasible regions)\nby a novel arithmetic three dimensional context coding procedure that\nefficiently utilizes rotational invariances present in the input data.\nState-of-the-art bits-per-voxel results are obtained on benchmark datasets.\n