Learning geometric differentials for matching 3D models to objects in a 2D image
US10733755B2 · kind B2 · utility
37Cited by
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24Claims
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Key dates
| Filing date | Jul 18, 2018 |
| Grant date | Aug 4, 2020 |
| Priority date | — |
| Expiry date | Oct 30, 2038 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06T2207/20084
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A method aligns, with an artificial neural network, a three-dimensional (3D) model to an object in a 2D image. The method includes detecting, with an object detector, the object from the 2D image. The method also includes estimating a geodesic distance value between the object and multiple discretized poses of the 3D model. The method further includes selecting a discretized pose of the multiple discretized poses corresponding to a smallest geodesic distance value. The method still further includes propagating pose parameters of the selected discretized pose of the 3D model to the object.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.