Gesture recognition is an emerging cross-discipline research field, which aims at interpreting human gestures and associating them to a well-defined meaning. It has been used as a mean for supporting human to machine interaction in several applications of robotics, artificial intelligence, and machine learning. In this paper, we propose a system able to recognize human body gestures which implements a constrained training set reduction technique. This allows the system for a real-time execution. The system has been tested on a publicly available dataset of 7,000 gestures, and experimental results have highlighted that at the cost of a little decrease in the maximum achievable recognition accuracy, the required time for recognition can be dramatically reduced.

Milazzo, F., Gentile, V., Sorce, S., Gentile, A. (2017). Real-time Body Gestures Recognition using Training Set Constrained Reduction. In L.T. Barolli (a cura di), Proceedings of the 11th International Conference on Complex, Intelligent and Software Intensive System (CISIS 2017) (pp. 216-224) [10.1007/978-3-319-61566-0_21].

Real-time Body Gestures Recognition using Training Set Constrained Reduction

MILAZZO, Fabrizio
;
Gentile, Vito;SORCE, Salvatore;GENTILE, Antonio
2017-01-01

Abstract

Gesture recognition is an emerging cross-discipline research field, which aims at interpreting human gestures and associating them to a well-defined meaning. It has been used as a mean for supporting human to machine interaction in several applications of robotics, artificial intelligence, and machine learning. In this paper, we propose a system able to recognize human body gestures which implements a constrained training set reduction technique. This allows the system for a real-time execution. The system has been tested on a publicly available dataset of 7,000 gestures, and experimental results have highlighted that at the cost of a little decrease in the maximum achievable recognition accuracy, the required time for recognition can be dramatically reduced.
2017
978-3-319-61565-3
Milazzo, F., Gentile, V., Sorce, S., Gentile, A. (2017). Real-time Body Gestures Recognition using Training Set Constrained Reduction. In L.T. Barolli (a cura di), Proceedings of the 11th International Conference on Complex, Intelligent and Software Intensive System (CISIS 2017) (pp. 216-224) [10.1007/978-3-319-61566-0_21].
File in questo prodotto:
File Dimensione Formato  
CISIS2017_final.pdf

accesso aperto

Descrizione: Articolo principale
Tipologia: Versione Editoriale
Dimensione 573.31 kB
Formato Adobe PDF
573.31 kB Adobe PDF Visualizza/Apri
CISIS2017_Front Cover + TOC.pdf

accesso aperto

Descrizione: Front Cover + TOC
Dimensione 324.66 kB
Formato Adobe PDF
324.66 kB Adobe PDF Visualizza/Apri

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10447/229282
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 2
  • ???jsp.display-item.citation.isi??? 0
social impact