Multi-object detection and recognition using exclusive non-maximum suppression (eNMS) and classification in cluttered scenes
US9165369B1 · kind B1 · utility
Assignee
Inventors
Key dates
| Filing date | Mar 12, 2014 |
| Grant date | Oct 20, 2015 |
| Priority date | — |
| Expiry date | Apr 9, 2034 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06V10/255
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Described is a system for multi-object detection and recognition in cluttered scenes. The system receives an image patch containing multiple objects of interest as input. The system evaluates a likelihood of existence of an object of interest in each sub-window of a set of overlapping sub-windows. A confidence map having confidence values corresponding to the sub-windows is generated. A non-maxima suppression technique is applied to the confidence map to eliminate sub-windows having confidence values below a local maximum confidence value. A global maximum confidence value is determined for a sub-window corresponding to a location of an instance of an object of interest in the image patch. The sub-window corresponding to the location of the instance of the object of interest is removed from the confidence map. The system iterates until a predetermined stopping criteria is met. Finally, detection information related to multiple instances of the object of interest is output.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.