Improving performance of image recognition algorithms by pruning features, image scaling, and spatially constrained feature matching
US8705876B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Dec 2, 2010 |
| Grant date | Apr 22, 2014 |
| Priority date | — |
| Expiry date | Jul 21, 2031 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06V10/757
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A method for feature matching in image recognition is provided. First, image scaling may be based on a feature distribution across scale spaces for an image to estimate image size/resolution, where peak(s) in the keypoint distribution at different scales is used to track a dominant image scale and roughly track object sizes. Second, instead of using all detected features in an image for feature matching, keypoints may be pruned based on cluster density and/or the scale level in which the keypoints are detected. Keypoints falling within high-density clusters may be preferred over features falling within lower density clusters for purposes of feature matching. Third, inlier-to-outlier keypoint ratios are increased by spatially constraining keypoints into clusters in order to reduce or avoid geometric consistency checking for the image.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.