Utilizing a segmentation neural network to process initial object segmentations and object user indicators within a digital image to generate improved object segmentations
US11676279B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Dec 18, 2020 |
| Grant date | Jun 13, 2023 |
| Priority date | — |
| Expiry date | Feb 19, 2041 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06T2207/20092
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
The present disclosure relates to systems, non-transitory computer-readable media, and methods that utilize a deep neural network to process object user indicators and an initial object segmentation from a digital image to efficiently and flexibly generate accurate object segmentations. In particular, the disclosed systems can determine an initial object segmentation for the digital image (e.g., utilizing an object segmentation model or interactive selection processes). In addition, the disclosed systems can identify an object user indicator for correcting the initial object segmentation and generate a distance map reflecting distances between pixels of the digital image and the object user indicator. The disclosed systems can generate an image-interaction-segmentation triplet by combining the digital image, the initial object segmentation, and the distance map. By processing the image-interaction-segmentation triplet utilizing the segmentation neural network, the disclosed systems can provide an updated object segmentation for display to a client device.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.