Object identification in bird's-eye view reference frame with explicit depth estimation co-training
US12266190B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Aug 9, 2022 |
| Grant date | Apr 1, 2025 |
| Priority date | — |
| Expiry date | Jun 27, 2043 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06V30/18086
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
The described aspects and implementations enable efficient detection and classification of objects with machine learning models that deploy a bird's-eye view representation and are trained using depth ground truth data. In one implementation, disclosed are system and techniques that include obtaining images, generating, using a first neural network (NN), feature vectors (FVs) and depth distributions pixels of images, wherein the first NN is trained using training images and a depth ground truth data for the training images. The techniques further include obtaining a feature tensor (FT) in view of the FVs and the depth distributions, and processing the obtained FTs, using a second NN, to identify one or more objects depicted in the images.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.