Neural network object pose determination
US12073588B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Sep 24, 2021 |
| Grant date | Aug 27, 2024 |
| Priority date | — |
| Expiry date | Nov 8, 2042 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06T2210/12
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A camera is positioned to obtain an image of an object. The image is input to a neural network that outputs a three-dimensional (3D) bounding box for the object relative to a pixel coordinate system and object parameters. Then a center of a bottom face of the 3D bounding box is determined in pixel coordinates. The bottom face of the 3D bounding box is located in a ground plane in the image. Based on calibration parameters for the camera that transform pixel coordinates into real-world coordinates, a) a distance from the center of the bottom face of the 3D bounding box to the camera relative to a real-world coordinate system and b) an angle between a line extending from the camera to the center of the bottom face of the 3D bounding box and an optical axis of the camera are determined. The calibration parameters include a camera height relative to the ground plane, a camera focal distance, and a camera tilt relative to the ground plane. A six degree-of-freedom (6DoF) pose for the object is determined based on the object parameters, the distance, and the angle.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.