Gesture Recognition System For Isolated Word Sign Language Based On key-Point Trajectory Matrix

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.