Fusing deep learning and geometric constraint for image-based localization
US11227406B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Feb 28, 2020 |
| Grant date | Jan 18, 2022 |
| Priority date | — |
| Expiry date | Apr 15, 2040 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06V2201/12
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A computer-implemented method, comprising applying training images of an environment divided into zones to a neural network, and performing classification to label a test image based on a closest zone of the zones; extracting a feature from retrieved training images and pose information of the test image that match the closest zone; performing bundle adjustment on the extracted feature by triangulating map points for the closest zone to generate a reprojection error, and minimizing the reprojection error to determine an optimal pose of the test image; and for the optimal pose, providing an output indicative of a location or probability of a location of the test image at the optimal pose within the environment.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.