Feature extraction and machine learning for automated metadata analysis
US10878296B2 · kind B2 · utility
Assignee
Inventor
Key dates
| Filing date | Apr 12, 2019 |
| Grant date | Dec 29, 2020 |
| Priority date | — |
| Expiry date | Jun 26, 2039 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06V2201/10
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
The invention relates to image processing systems, methods, and storage media for recognizing a scene type. The invention performs dynamic content analysis to extract features from an image and creates labels that include a text-based description of the items and the environment of the image. The invention then trains multiple predictive models and determines characterization labels for the image or scene. The invention can create multi-label classifications as well as multi-class classifiers. The text-based labels created by the invention extend generic classification labels into a domain-specific manner of defining and naming groups of images. The characterizing labels can be tagged to the image as metadata for further organization and consumption of the images or scenes.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.