The Automatic Recognition of Isolated Sign Language Signs Based on Gesture Components and DTW Algorithm

Author presents sign language features that can provide the basis of the sign language automatic recognition systems. Using parameters like position, velocity, angular orientation, fingers bending and the conventional or derivative dynamic time warping algorithms classification of 95 signs from the AUSLAN database was performed. Depending on the number of parameters used in classification different accuracy values were obtained (defined as the ratio of correctly recognized gestures to all gestures from test set), with the highest value 87.7% for the case of classification based on all the features and the derivative dynamic time warping method.