Systems and methods utilizing a machine learning model for generating defocus blur effects
US11094075B1 · kind B1 · utility
Assignee
Inventors
Key dates
| Filing date | Jul 19, 2018 |
| Grant date | Aug 17, 2021 |
| Priority date | — |
| Expiry date | Jan 11, 2039 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06T2207/20084
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
In one embodiment, a system may access a training sample that includes training images and corresponding training depth maps of a scene, with the training images being associated with different predetermined viewpoints of the scene. The system may generate elemental images of the scene by processing the training images and the training depth maps using a machine-learning model. The elemental images are associated with more viewpoints of the scene than the predetermined viewpoints associated with the training images. The system may update the machine-learning model based on a comparison between the generated elemental images of the scene and target elemental images that are each associated with a predetermined viewpoint. The updated machine-learning model is configured to generate elemental images of a scene of interest based on input images and corresponding depth maps of the scene of interest from different viewpoints.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.