Online, Interactive Learning of Gestures for Human/Robot Interfaces

Authors:

Christopher Lee

Yangsheng Xu

Summary:

Goal: Provde better interactivity and control over robots (effectiveness of tele-operation).

Cyberglove is used record hand gesture input from the users. Hidden Markov model is used to recognize the gestures.

- Users perform a series of gesture

- HMM train on the gesture if they classify them into one of the existing gestures and perform the related action.

- if HMM is not able to classify,

- asks the user to disambiguate and train.

- new gesture added by the user.

Discussion:

the preprocessing procedure is very interesting. It is applicable to PowerGlove++ project by Drew & co.

Comments: Franck