HMM based automatic Arabic sign language translator using Kinect

In this paper, a new Arabic sign language automatic translator is presented. The translator is based on Hidden Markov Models (HMM´s). The features used in recognition are 3D information detected using Microsoft Kinect Sensor depth camera. The system was trained to recognize 40 signs from standard Arabic sign language. A go-stop scheme is presented to handle sequences of signs which construct sentences in real-time. The recognition success rate based on the new methodology is above 90 percent with real time performance on a PC.