Data-driven ghosting using deep imitation learning
US12165395B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Dec 4, 2017 |
| Grant date | Dec 10, 2024 |
| Priority date | — |
| Expiry date | Jul 17, 2040 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06V10/62
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
One embodiment provides a method, comprising: training, using deep imitation learning, a neural network associated with a predetermined ghosting model to predict player movements for at least one player during at least one sequence in a game; receiving, at an information handling device, tracking data associated with a player movement path for at least one player during the at least one sequence; analyzing, using a processor, the tracking data to determine at least one feature associated with the at least one player at a plurality of predetermined time points during the at least one sequence; and determining, using the predetermined ghosting model and the at least one feature, a ghosted movement path for the at least one player beginning from one of the plurality of predetermined time points. Other aspects are described and claimed.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.