Method for determining similarity of objects represented in images
US9436895B1 · kind B1 · utility
Assignee
Inventors
Key dates
| Filing date | Apr 3, 2015 |
| Grant date | Sep 6, 2016 |
| Priority date | — |
| Expiry date | Apr 3, 2035 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06V20/52
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A method re-identifies objects in a pair of images by applying a convolutional neural network (CNN). Each layer in the network operates on an output of a previous layer. The layers include a first convolutional layer and a first max pooling layer to determine a feature map, a cross-input neighborhood differences layer to produce neighborhood difference maps, a patch summary layer to produce patch summary feature maps, a first fully connected layer to produce a feature vector representing higher order relationships in the patch summary feature maps, a second fully connected layer to produce two scores representing positive pair and negative pair classes, and a softmax layer to produce positive pair and negative pair probabilities. Then, the positive pair probability is output to signal whether the two images represent the same object or not.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.