Method and system for gesture category recognition and training using a feature vector
US6249606A · kind A · utility
Assignee
Inventors
Key dates
| Filing date | Feb 19, 1998 |
| Grant date | Jun 19, 2001 |
| Priority date | — |
| Expiry date | Feb 19, 2018 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06V30/333
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A computer implemented method and system for gesture category recognition and training. Generally, a gesture is a hand or body initiated movement of a cursor directing device to outline a particular pattern in particular directions done in particular periods of time. The present invention allows a computer system to accept input data, originating from a user, in the form gesture data that are made using the cursor directing device. In one embodiment, a mouse device is used, but the present invention is equally well suited for use with other cursor directing devices (e.g., a track ball, a finger pad, an electronic stylus, etc.). In one embodiment, gesture data is accepted by pressing a key on the keyboard and then moving the mouse (with mouse button pressed) to trace out the gesture. Mouse position information and time stamps are recorded. The present invention then determines a multi-dimensional feature vector based on the gesture data. The feature vector is then passed through a gesture category recognition engine that, in one implementation, uses a radial basis function neural network to associate the feature vector to a pre-existing gesture category. Once identified, a set of us…
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.