Method for salient object segmentation of image by aggregating multi-linear exemplar regressors
US10387748B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Oct 24, 2017 |
| Grant date | Aug 20, 2019 |
| Priority date | — |
| Expiry date | Feb 23, 2038 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06T2207/20156
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Provided is a method for salient object segmentation of an image by aggregating a multi-linear exemplar regressors, including: analyzing and summarizing visual attributes and features of a salient object and a non-salient object using background prior and constructing a quadratic optimization problem, calculating an initial saliency probability map, selecting a most trusted foreground and a background seed point, performing manifold preserving foreground propagation, generating a final foreground probability map; generating a candidate object set for the image via an objectness adopting proposal, using a shape feature, a foregroundness and an attention feature to characterize each candidate object, training the linear exemplar regressors for each training image to characterize a particular saliency pattern of the image; aggregating a plurality of linear exemplar regressors, calculating saliency values for the candidate object set of a test image, and forming an image salient object segmentation model capable of processing various complex scenarios.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.