Methods and apparatus for finger detection and separation on a touch sensor panel using machine learning models
US11301099B1 · kind B1 · utility
Assignee
Inventors
Key dates
| Filing date | Mar 27, 2020 |
| Grant date | Apr 12, 2022 |
| Priority date | — |
| Expiry date | Mar 27, 2040 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06F3/0445
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Finger detection and separation techniques on a multi-touch touch sensor panel can be improved using machine learning models (particularly for touch sensor panels with relatively low signal-to-noise ratio). In some examples, a machine learning model can be used to process an input patch to disambiguate whether the input patch corresponds to one contact or two contacts. In some examples, the machine learning model can be implemented using a neural network. The neural network can receive a sub-image including an input patch as an input, and can output a number of contacts. In some examples, the neural network can output one or more sub-image masks representing the one or more contacts.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.