Vision-Based Portuguese Sign Language Recognition System

• Tipo: Artigo em Livro de Atas de Conferência Internacional
• Data: 2014

Autores

trigueiros, p (Autor) Outra; ribeiro, fr (Autor) Outra; reis, lp (Autor) FCUP

Ata de Conferência Internacional

Título: NEW PERSPECTIVES IN INFORMATION SYSTEMS AND TECHNOLOGIES, VOL 1

Páginas: 605-617

World Conference on Information Systems and Technologies (WorldCIST)

Funchal, PORTUGAL, APR 15-18, 2014

Indexação

ISI Web of Knowledge - 10 Citações

Scopus - 18 Citações

Outras Informações

ID Authenticus: P-009-PQ3

DOI: 10.1007/978-3-319-05951-8_57

Abstract (EN): Vision-based hand gesture recognition is an area of active current research in computer vision and machine learning. Being a natural way of human interaction, it is an area where many researchers are working on, with the goal of making human computer interaction (HCI) easier and natural, without the need for any extra devices. So, the primary goal of gesture recognition research is to create systems, which can identify specific human gestures and use them, for example, to convey information. For that, vision-based hand gesture interfaces require fast and extremely robust hand detection, and gesture recognition in real time. Hand gestures are a powerful human communication modality with lots of potential applications and in this context we have sign language recognition, the communication method of deaf people. Sign languages are not standard and universal and the grammars differ from country to country. In this paper, a real-time system able to interpret the Portuguese Sign Language is presented and described. Experiments showed that the system was able to reliably recognize the vowels in real-time, with an accuracy of 99.4% with one dataset of features and an accuracy of 99.6% with a second dataset of features. Although the implemented solution was only trained to recognize the vowels, it is easily extended to recognize the rest of the alphabet, being a solid foundation for the development of any vision-based sign language recognition user interface system.

Idioma: Inglês

Tipo (Avaliação Docente): Científica

Nº de páginas: 13