Hands gestures recognition, by means of measuring apparatus, can provide a new way of human-computer interaction. Controlling different devices or speaking through a speech synthesizer can be time saving as well as an aid for impaired persons. In this work we performed the classification of 19 different gestures, evaluating three different methodologies: Support Vector Machines, Mahalanobis and Euclidean based classifiers
Saggio, G., Cavallo, P., Fabrizio, A., Ibe, S. (2011). Gesture recognition adopting the HITEG data glove to provide a new way of communication. ??????? it.cilea.surplus.oa.citation.tipologie.CitationProceedings.prensentedAt ??????? International Symposium on Applied Sciences in Biomedical and Communication Technologies (ISABEL), Barcelona, Catalonia (Spain).
Gesture recognition adopting the HITEG data glove to provide a new way of communication
SAGGIO, GIOVANNI;
2011-10-01
Abstract
Hands gestures recognition, by means of measuring apparatus, can provide a new way of human-computer interaction. Controlling different devices or speaking through a speech synthesizer can be time saving as well as an aid for impaired persons. In this work we performed the classification of 19 different gestures, evaluating three different methodologies: Support Vector Machines, Mahalanobis and Euclidean based classifiers| File | Dimensione | Formato | |
|---|---|---|---|
|
gesture rec [rev].pdf
accesso aperto
Descrizione: Articolo principale
Dimensione
485.53 kB
Formato
Adobe PDF
|
485.53 kB | Adobe PDF | Visualizza/Apri |
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
