The purpose of the developed system is the realization of a gesture recognizer, applied to a user interface. We tried to get fast and easy software for user, without leaving out reliability and using instruments available to common user: a PC and a webcam. The gesture detection is based on well-known artificial vision techniques, as the tracking algorithm by Lucas and Kanade. The paths, opportunely selected, are recognized by a double layered architecture of multilayer perceptrons. The realized system is efficiency and has a good robustness, paying attention to an adequate learning of gesture vocabulary both for the user and for system.
Artificial Neural Networks based Symbolic Gesture Interface / Iacopino, C; Montesanto, A; Dragoni, Aldo Franco; Puliti, Paolo. - STAMPA. - (2008), pp. 364-369. (Intervento presentato al convegno SIGMAP 2008 - Proceedings of the International Conference on Signal Processing and Multimedia Applications tenutosi a Porto, Portogallo nel 26-29 Luglio 2008).
Artificial Neural Networks based Symbolic Gesture Interface
DRAGONI, Aldo Franco;PULITI, Paolo
2008-01-01
Abstract
The purpose of the developed system is the realization of a gesture recognizer, applied to a user interface. We tried to get fast and easy software for user, without leaving out reliability and using instruments available to common user: a PC and a webcam. The gesture detection is based on well-known artificial vision techniques, as the tracking algorithm by Lucas and Kanade. The paths, opportunely selected, are recognized by a double layered architecture of multilayer perceptrons. The realized system is efficiency and has a good robustness, paying attention to an adequate learning of gesture vocabulary both for the user and for system.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
