Semantically-consistent augmented training data for traffic light detection
US11410433B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Mar 31, 2020 |
| Grant date | Aug 9, 2022 |
| Priority date | — |
| Expiry date | Feb 3, 2041 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06T2207/10032
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Methods, systems, and non-transitory computer-readable media for generating augmented data to train a deep neural network to detect traffic lights in image data. The method includes receiving a plurality of real roadway scene images and selecting a subset of the plurality of real roadway scene images. The method also includes selecting an image from the subset and determining a distribution indicting how likely each location in the selected image can contain a traffic light. The method further includes selecting a location in the selected image by sampling the distribution and superimposing a traffic light image onto the selected image at the selected location to generate an augmented roadway scene image. The method also includes processing each image in the subset to generate a plurality of augmented roadway scene images. The method further includes training a deep neural network model using the pluralities of real and augmented roadway scene images.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.