Content-adaptive non-uniform image downsampling using predictive auxiliary convolutional neural network
US11170470B1 · kind B1 · utility
Assignee
Inventors
Key dates
| Filing date | Dec 6, 2019 |
| Grant date | Nov 9, 2021 |
| Priority date | — |
| Expiry date | Jan 7, 2040 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06T2207/20084
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Techniques are described for content-adaptive downsampling of digital images and videos for computer vision operations, such as semantic segmentation. A computer vision system comprises a memory, one or more processors operably coupled to the memory and a downsampling module configured for execution by the one or more processors to perform, based on a non-uniform sampling model trained to predict content-aware sampling parameters, downsampling input image data to generate downsampled image data. A segmentation module is configured for execution by the one or more processors to perform segmentation on the downsampled image to produce a segmentation result, such as a feature map that assigns pixels of the downsampled image data to object classes. An upsampling module is configured for execution by the one or more processors to perform upsampling according to the segmentation result to produce upsampled image data.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.