Subcategory-aware convolutional neural networks for object detection
US9965719B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Nov 3, 2016 |
| Grant date | May 8, 2018 |
| Priority date | — |
| Expiry date | Nov 3, 2036 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06T2207/30261
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A computer-implemented method for detecting objects by using subcategory-aware convolutional neural networks (CNNs) is presented. The method includes generating object region proposals from an image by a region proposal network (RPN) which utilizes subcategory information, and classifying and refining the object region proposals by an object detection network (ODN) that simultaneously performs object category classification, subcategory classification, and bounding box regression. The image is an image pyramid used as input to the RPN and the ODN. The RPN and the ODN each include a feature extrapolating layer to detect object categories with scale variations among the objects.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.