Dual cross-media relevance model for image annotation
US8571850B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Dec 13, 2007 |
| Grant date | Oct 29, 2013 |
| Priority date | — |
| Expiry date | Sep 14, 2031 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06F40/242
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A dual cross-media relevance model (DCMRM) is used for automatic image annotation. In contrast to the traditional relevance models which calculate the joint probability of words and images over a training image database, the DCMRM model estimates the joint probability by calculating the expectation over words in a predefined lexicon. The DCMRM model may be advantageous because a predefined lexicon potentially has better behavior than a training image database. The DCMRM model also takes advantage of content-based techniques and image search techniques to define the word-to-image and word-to-word relations involved in image annotation. Both relations can be estimated by using image search techniques on the web data as well as available training data.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.