| Paper ID | IVMSP-16.1 |
| Paper Title |
G-ARRAYS: GEOMETRIC ARRAYS FOR EFFICIENT POINT CLOUD PROCESSING |
| Authors |
Hoda Roodaki, Masoud Dehyadegari, K. N. Toosi University of technology, Iran; Mahdi Nazm Bojnordi, School of Computing, University of Utah, United States |
| Session | IVMSP-16: Point Clouds and Depth |
| Location | Gather.Town |
| Session Time: | Wednesday, 09 June, 15:30 - 16:15 |
| Presentation Time: | Wednesday, 09 June, 15:30 - 16:15 |
| Presentation |
Poster
|
| Topic |
Image, Video, and Multidimensional Signal Processing: [IVCOM] Image & Video Communications |
| IEEE Xplore Open Preview |
Click here to view in IEEE Xplore |
| Virtual Presentation |
Click here to watch in the Virtual Conference |
| Abstract |
With the increasing demand for 3D modeling by the emerging immersive applications, the 3D point cloud has become an essential representation format for processing 3D images and video. Because of the inherent sparsity in 3D data and the significant memory requirements for representing points, point cloud processing is a challenging task. In this paper, we propose a novel data structure for representing point clouds with a reduced memory requirement and a faster lookup than the state-of-the-art formats. The proposed format is examined for temporal encoding in geometric point cloud compression. Our simulation results show that the proposed temporal prediction enhances the compression rate and quality by 13-33% as compared to MPEG G-PCC. Moreover, the proposed data structure provides 16-54x faster point lookup operations and more than 1.4x reduction in memory consumption compared to the octree structure used in the MPEG G-PCC. |
