Method and system for efficiently mining dataset essentials with bootstrapping strategy in 6DOF pose estimate of 3D objects
US10803619B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Mar 13, 2017 |
| Grant date | Oct 13, 2020 |
| Priority date | — |
| Expiry date | Jul 17, 2037 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06T2207/30244
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A method for identifying a feature in a first image comprises establishing an initial database of image triplets, and in a pose estimation processor, training a deep learning neural network using the initial database of image triplets, calculating a pose for the first image using the deep learning neural network, comparing the calculated pose to a validation database populated with images data to identify an error case in the deep learning neural network, creating a new set of training data including a plurality of error cases identified in a plurality of input images and retraining the deep learning neural network using the new set of training data. The deep learning neural network may be iteratively retrained with a series of new training data sets. Statistical analysis is performed on a plurality of error cases to select a subset of the error cases included in the new set of training data.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.