Determining traversable space from single images
US11741675B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Mar 5, 2021 |
| Grant date | Aug 29, 2023 |
| Priority date | — |
| Expiry date | Mar 5, 2041 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06T2219/2004
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A model predicts the geometry of both visible and occluded traversable surfaces from input images. The model may be trained from stereo video sequences, using camera poses, per-frame depth, and semantic segmentation to form training data, which is used to supervise an image to image network. In various embodiments, the model is applied to a single RGB image depicting a scene to produce information describing traversable space of the scene that includes occluded traversable. The information describing traversable space can include a segmentation mask of traversable space (both visible and occluded) and non-traversable space and a depth map indicating an estimated depth to traversable surfaces corresponding to each pixel determined to correspond to traversable space.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.