Reconstructing three-dimensional scenes portrayed in digital images utilizing point cloud machine-learning models
US11443481B1 · kind B1 · utility
Assignee
Inventors
Key dates
| Filing date | Feb 26, 2021 |
| Grant date | Sep 13, 2022 |
| Priority date | — |
| Expiry date | Feb 26, 2041 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06T2210/56
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
This disclosure describes implementations of a three-dimensional (3D) scene recovery system that reconstructs a 3D scene representation of a scene portrayed in a single digital image. For instance, the 3D scene recovery system trains and utilizes a 3D point cloud model to recover accurate intrinsic camera parameters from a depth map of the digital image. Additionally, the 3D point cloud model may include multiple neural networks that target specific intrinsic camera parameters. For example, the 3D point cloud model may include a depth 3D point cloud neural network that recovers the depth shift as well as include a focal length 3D point cloud neural network that recovers the camera focal length. Further, the 3D scene recovery system may utilize the recovered intrinsic camera parameters to transform the single digital image into an accurate and realistic 3D scene representation, such as a 3D point cloud.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.