3D point cloud compression system based on multi-scale structured dictionary learning
US11836954B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Mar 13, 2023 |
| Grant date | Dec 5, 2023 |
| Priority date | — |
| Expiry date | Mar 13, 2043 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06T9/40
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
In a 3D point cloud compression system based on multi-scale structured dictionary learning, a point cloud data partition module outputs a voxel set and a set of blocks of voxels of different scales. A geometric information encoding module outputs an encoded geometric information bit stream. A geometric information decoding module outputs decoded geometric information. An attribute signal encoding module outputs a sparse coding coefficient matrix and a learned multi-scale structured dictionary. An attribute signal compression module outputs a compressed attribute signal bit stream. An attribute signal decoding module outputs decoded attribute signals. A 3D point cloud reconstruction module completes reconstruction. The system is applicable to lossless geometric and lossy attribute compression of point cloud signals. Based on the natural hierarchical partitioning structure of point cloud signals, the system gradually improves the reconstruction quality of high-frequency details in the signals from coarse scale to fine scale, and achieves significant gains.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.