Systems and methods for rear signal identification using machine learning
US10691962B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Sep 22, 2017 |
| Grant date | Jun 23, 2020 |
| Priority date | — |
| Expiry date | May 22, 2038 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06V2201/08
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
System, methods, and other embodiments described herein relate to identifying rear indicators of a nearby vehicle. In one embodiment, a method includes, in response to detecting a nearby vehicle, capturing signal images of a rear portion of the nearby vehicle. The method includes computing a braking state for brake lights of the nearby vehicle that indicates whether the brake lights are presently active by analyzing the signal images according to a brake classifier. The method includes computing a turn state for rear turn signals of the nearby vehicle that indicates which of the turn signals are presently active by analyzing regions of interest from the signal images according to a turn classifier. The brake classifier and the turn classifier are comprised of a convolutional neural network and a long short-term memory recurrent neural network (LSTM-RNN). The method includes providing electronic outputs identifying the braking state and the turn state.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.