Automated gesture identification using neural networks
US11087488B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | May 23, 2019 |
| Grant date | Aug 10, 2021 |
| Priority date | — |
| Expiry date | May 31, 2039 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N3/006
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Disclosed are methods, apparatus and systems for gesture recognition based on neural network processing. One exemplary method for identifying a gesture communicated by a subject includes receiving a plurality of images associated with the gesture, providing the plurality of images to a first 3-dimensional convolutional neural network (3D CNN) and a second 3D CNN, where the first 3D CNN is operable to produce motion information, where the second 3D CNN is operable to produce pose and color information, and where the first 3D CNN is operable to implement an optical flow algorithm to detect the gesture, fusing the motion information and the pose and color information to produce an identification of the gesture, and determining whether the identification corresponds to a singular gesture across the plurality of images using a recurrent neural network that comprises one or more long short-term memory units.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.