Clustering large database of images using multilevel clustering approach for optimized face recognition process
US9922240B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Sep 6, 2017 |
| Grant date | Mar 20, 2018 |
| Priority date | — |
| Expiry date | Sep 6, 2037 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06V10/762
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
In multilevel clustering for a face recognition process, the first stage clustering is performed on each computing node, using the first x vector coefficients. From the resulting k clusters created in the first stage, a limited number of clusters are selected on which the second stage clustering is performed, using the next y vector coefficients. The search for a matching image is then limited to these selected clusters. Computational costs are reduced at the first stage clustering by using just the first x vector coefficients. Computational costs for the second stage clustering are also reduced by performing the second stage only with the limited number of clusters on a limited number of computing nodes. In this manner, the overall computational costs in the face recognition process is significantly reduced while maintaining a desired level of accuracy.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.