Hidden Markov model-based gesture recognition with FMCW radar
US10514770B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Jun 16, 2017 |
| Grant date | Dec 24, 2019 |
| Priority date | — |
| Expiry date | Jun 16, 2037 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N7/01
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A gesture recognition system is shown using a 77 GHz FMCW radar system. The signature of a gesturing hand is measured to construct an energy distribution in velocity space over time. A gesturing hand is fundamentally a dynamical system with unobservable “state” (i.e. the type of the gesture) which determines the sequence of associated observable velocity-energy distributions, therefore a Hidden Markov Model is used to for gesture recognition. A method for reducing the length of the feature vectors by a factor of 12 is also shown, by re-parameterizing the feature vectors in terms of a sum of Gaussians without decreasing the recognition performance.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.