Hierarchical conditional random field model for labeling and segmenting images
US9443314B1 · kind B1 · utility
25Cited by
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Key dates
| Filing date | Mar 29, 2012 |
| Grant date | Sep 13, 2016 |
| Priority date | — |
| Expiry date | May 22, 2035 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06V20/10
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
An image processing system automatically segments and labels an image using a hierarchical classification model. A global classification model determines initial labels for an image based on features of the image. A label-based descriptor is generated based on the initial labels. A local classification model is then selected from a plurality of learned local classification model based on the label-based descriptor. The local classification model is applied to the features of the input image to determined refined labels. The refined labels are stored in association with the input image.
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