Enhanced training of machine learning systems based on automatically generated realistic gameplay information
US11532172B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Jul 10, 2020 |
| Grant date | Dec 20, 2022 |
| Priority date | — |
| Expiry date | Nov 6, 2040 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N3/084
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Systems and methods for enhanced training of machine learning systems based on automatically generated visually realistic gameplay. An example method includes obtaining electronic game data that includes rendered images and associated annotation information, the annotation information identifying features included in the rendered images to be learned, and the electronic game data being generated by a video game associated with a particular sport. Machine learning models are trained based on the obtained electronic game data, with training including causing the machine learning models to output annotation information based on associated input of a rendered image. Real-world gameplay data is obtained, with the real-world gameplay data being images of real-world gameplay of the particular sport. The obtained real-world gameplay data is analyzed based on the trained machine learning models. Analyzing includes extracting features from the real-world gameplay data using the machine learning models.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.