Iteratively applying neural networks to automatically identify pixels of salient objects portrayed in digital images
US11244195B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | May 1, 2018 |
| Grant date | Feb 8, 2022 |
| Priority date | — |
| Expiry date | May 21, 2040 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06V10/82
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
The present disclosure relates to systems, method, and computer readable media that iteratively apply a neural network to a digital image at a reduced resolution to automatically identify pixels of salient objects portrayed within the digital image. For example, the disclosed systems can generate a reduced-resolution digital image from an input digital image and apply a neural network to identify a region corresponding to a salient object. The disclosed systems can then iteratively apply the neural network to additional reduced-resolution digital images (based on the identified region) to generate one or more reduced-resolution segmentation maps that roughly indicate pixels of the salient object. In addition, the systems described herein can perform post-processing based on the reduced-resolution segmentation map(s) and the input digital image to accurately determine pixels that correspond to the salient object.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.