Two-stage depth estimation machine learning algorithm and spherical warping layer for equi-rectangular projection stereo matching
US11810311B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Oct 31, 2020 |
| Grant date | Nov 7, 2023 |
| Priority date | — |
| Expiry date | Oct 15, 2041 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06T2207/20084
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A system and method is disclosed having an end-to-end two-stage depth estimation deep learning framework that takes one spherical color image and estimate dense spherical depth maps. The contemplated framework may include a view synthesis (stage 1) and a multi-view stereo matching (stage 2). The combination of the two-stage process may provide the advantage of the geometric constraints from stereo matching to improve depth map quality, without the need of additional input data. It is also contemplated that a spherical warping layer may be used to integrate multiple spherical features volumes to one cost volume with uniformly sampled inverse depth for the multi-view spherical stereo matching stage. The two-stage spherical depth estimation system and method may be used in various applications including virtual reality, autonomous driving and robotics.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.