Relevance maximizing, iteration minimizing, relevance-feedback, content-based image retrieval (CBIR)
US7546293B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Jul 17, 2006 |
| Grant date | Jun 9, 2009 |
| Priority date | — |
| Expiry date | Feb 23, 2027 |
Classification
- Technology area (CPC Y)Emerging Cross-Sectional Technologies
- CPC primaryY10S707/99948
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
An implementation of a technology, described herein, for relevance-feedback, content-based image retrieval minimizes the number of iterations for user feedback regarding the semantic relevance of exemplary images while maximizing the resulting relevance of each iteration. One technique for accomplishing this is to use a Bayesian classifier to treat positive and negative feedback examples with different strategies. In addition, query refinement techniques are applied to pinpoint the users' intended queries with respect to their feedbacks. These techniques further enhance the accuracy and usability of relevance feedback. This abstract itself is not intended to limit the scope of this patent. The scope of the present invention is pointed out in the appending claims.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.