| Paper ID | SS-MRII.3 | ||
| Paper Title | REFINING THE BOUNDING VOLUMES FOR LOSSLESS COMPRESSION OF VOXELIZED POINT CLOUDS GEOMETRY | ||
| Authors | Emre Can Kaya, Tampere University, Finland; Sebastian Schwarz, Nokia Technologies, Germany; Ioan Tabus, Tampere University, Finland | ||
| Session | SS-MRII: Special Session: Models and representations for Immersive Imaging | ||
| Location | Area A | ||
| Session Time: | Wednesday, 22 September, 08:00 - 09:30 | ||
| Presentation Time: | Wednesday, 22 September, 08:00 - 09:30 | ||
| Presentation | Poster | ||
| Topic | Special Sessions: Models and Representations for Immersive Imaging | ||
| IEEE Xplore Open Preview | Click here to view in IEEE Xplore | ||
| Abstract | This paper describes a novel lossless compression method for point cloud geometry, building on a recent lossy compression method that aimed at reconstructing only the bounding volume of a point cloud. The proposed scheme starts by partially reconstructing the geometry from the two depthmaps associated to a single projection direction. The partial reconstruction obtained from the depthmaps is completed to a full reconstruction of the point cloud by sweeping section by section along one direction and encoding the points which were not contained in the two depthmaps. The main ingredient is a list-based encoding of the inner points (situated inside the feasible regions) by a novel arithmetic three dimensional context coding procedure that efficiently utilizes rotational invariances present in the input data. State-of-the-art bits-per-voxel results are obtained on benchmark datasets. | ||