Resumen

FAKHFAKH, Sana  y  JEMAA, Yousra Ben. Gesture Recognition System For Isolated Word Sign Language Based On key-Point Trajectory Matrix. Comp. y Sist. [online]. 2018, vol.22, n.4, pp.1415-1430.  Epub 10-Feb-2021. ISSN 2007-9737.  https://doi.org/10.13053/cys-22-4-3046.

This paper suggests a new system to help the deaf and the hearing-impaired community improve their connection with the hearing world and communicate freely. The most important thing in this system is how to help the users be free and finally have a more natural way of communication. For this reason, we present a new process based on two levels: a static-level aiming to extract the most head/hands key points and a dynamic-level with the objective of accumulating the key-point trajectory matrix. Also our proposed approach takes into account the signer-independence constraint. A SIGNUM database is applied in the classification stage and our system performances have improved with a 94.3% recognition rate. Furthermore, a reduction in time processing is obtained when the removing of redundant frame step is applied. The obtained results prove the superiority of our system compared to the state-of- the-art methods in terms of recognition rate and execution time.

Palabras llave : Sign language recognition; isolated word; signer-independence; particular filter; key-point trajectory matrix.

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