The proposed hand gesture recognition (HGR) system is designed to enhance human-computer interaction (HCI) and human-robot interaction (HRI), which are crucial areas of research aimed at improving the way humans interact with computer or robot systems. With the growing need for intelligent computers and robots in a range of applications, including healthcare, manufacturing, and education, both HCI and HRI have gained significant importance. In this context, the HGR system plays a vital role by enabling natural and intuitive communication between humans and technology through hand gestures. The presented system uses a single camera and efficient image processing techniques that enable real-time gesture detection. Unlike other methods, our approach employs a basic video camera, which is widely available on most computers, eliminating the need for expensive and specialized hardware.

A Real-time Hand Gesture Recognition System for Human-Computer and Human-Robot Interaction / Ponzi, V.; Iacobelli, E.; Napoli, C.; Starczewski, J.. - 3398:(2022), pp. 52-58. (Intervento presentato al convegno 2022 International Conference of Yearly Reports on Informatics, Mathematics, and Engineering, ICYRIME 2022 tenutosi a Catania; Italy).

A Real-time Hand Gesture Recognition System for Human-Computer and Human-Robot Interaction

Ponzi V.
Primo
Investigation
;
Iacobelli E.
Secondo
Software
;
Napoli C.
Penultimo
Supervision
;
2022

Abstract

The proposed hand gesture recognition (HGR) system is designed to enhance human-computer interaction (HCI) and human-robot interaction (HRI), which are crucial areas of research aimed at improving the way humans interact with computer or robot systems. With the growing need for intelligent computers and robots in a range of applications, including healthcare, manufacturing, and education, both HCI and HRI have gained significant importance. In this context, the HGR system plays a vital role by enabling natural and intuitive communication between humans and technology through hand gestures. The presented system uses a single camera and efficient image processing techniques that enable real-time gesture detection. Unlike other methods, our approach employs a basic video camera, which is widely available on most computers, eliminating the need for expensive and specialized hardware.
2022
2022 International Conference of Yearly Reports on Informatics, Mathematics, and Engineering, ICYRIME 2022
convolutional neural network; deep learning; hand gesture recognition; machine learning
04 Pubblicazione in atti di convegno::04b Atto di convegno in volume
A Real-time Hand Gesture Recognition System for Human-Computer and Human-Robot Interaction / Ponzi, V.; Iacobelli, E.; Napoli, C.; Starczewski, J.. - 3398:(2022), pp. 52-58. (Intervento presentato al convegno 2022 International Conference of Yearly Reports on Informatics, Mathematics, and Engineering, ICYRIME 2022 tenutosi a Catania; Italy).
File allegati a questo prodotto
File Dimensione Formato  
Ponzi_A-real_2022.pdf

accesso aperto

Tipologia: Versione editoriale (versione pubblicata con il layout dell'editore)
Licenza: Creative commons
Dimensione 1.41 MB
Formato Adobe PDF
1.41 MB Adobe PDF

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/11573/1683653
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 1
  • ???jsp.display-item.citation.isi??? ND
social impact