Sign Language Recognition opens to a wide research field with the aim of solving problems for the integration of deaf people in society. The goal of this research is to reduce the communication gap between hearing impaired users and other subjects, building an educational system for hearing impaired children. This project uses computer vision and machine learning algorithms to reach this objective. In this paper we analyze the image processing techniques for detecting hand gestures in video and we compare two approaches based on machine learning to achieve gesture recognition.
A computer vision method for the Italian finger spelling recognition / Bevilacqua, Vitoantonio; Biasi, Luigi; Pepe, Antonio; Mastronardi, Giuseppe; Caporusso, Nicholas (LECTURE NOTES IN COMPUTER SCIENCE). - In: Advanced Intelligent Computing Theories and Applications: 11th International Conference, ICIC 2015, Fuzhou, China, August 20-23, 2015. Proceedings, Part III / [a cura di] De-Shuang Huang; Kyungsook Han. - STAMPA. - Cham, CH : Springer, 2015. - ISBN 978-3-319-22052-9. - pp. 264-274 [10.1007/978-3-319-22053-6_28]
A computer vision method for the Italian finger spelling recognition
Bevilacqua, Vitoantonio;Biasi, Luigi;Pepe, Antonio;Mastronardi, Giuseppe;Caporusso, Nicholas
2015-01-01
Abstract
Sign Language Recognition opens to a wide research field with the aim of solving problems for the integration of deaf people in society. The goal of this research is to reduce the communication gap between hearing impaired users and other subjects, building an educational system for hearing impaired children. This project uses computer vision and machine learning algorithms to reach this objective. In this paper we analyze the image processing techniques for detecting hand gestures in video and we compare two approaches based on machine learning to achieve gesture recognition.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
