End-to-end saliency mapping via probability distribution prediction
US9830529B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Apr 26, 2016 |
| Grant date | Nov 28, 2017 |
| Priority date | — |
| Expiry date | Apr 26, 2036 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06V40/193
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A method for generating a system for predicting saliency in an image and method of use of the prediction system are described. Attention maps for each of a set of training images are used to train the system. The training includes passing the training images though a neural network and optimizing an objective function over the training set which is based on a distance measure computed between a first probability distribution computed for a saliency map output by the neural network and a second probability distribution computed for the attention map for the respective training image. The trained neural network is suited to generation of saliency maps for new images.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.