Machine learning-based seatbelt detection and usage recognition using fiducial marking
US12005855B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Jun 18, 2020 |
| Grant date | Jun 11, 2024 |
| Priority date | — |
| Expiry date | Jan 18, 2041 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06V10/82
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Systems and methods for machine learning based seatbelt position detection and classification. A number of fiducial markers are placed on a vehicle seatbelt. A camera or other sensor is placed within the vehicle, to capture images or other data relating positions of the fiducial markers when the seatbelt is in use. One or more models such as machine learning models may then determine the spatial positions of the fiducial markers from the captured image information, and determine the worn state of the seatbelt. In particular, the system may determine whether the seatbelt is being worn in one or more improper states, such as not being worn or being worn in an unsafe or dangerous manner, and if so, the system may alert the vehicle to take corrective action. In this manner, the system provides constant and real-time monitoring of seatbelts to improve seatbelt usage and safety.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.