An Automated Method for Evaluating the Accuracy of ASL Static Gestures

Within the past few years, research involving gesture recognition has flourished and has led to new and improved methods assisting people who communicate with sign language. Although numerous approaches have been developed for recognizing gestures, very little attention has been focused on correcting the placement of the fingers after the gesture has been performed. In ASL the placement of the fingers is very important considering a slight misplacement conveys a completely different word, letter, or meaning. We present a new method in correcting the placement of static American Sign Language (ASL) gestures using existing algorithms and feature recognition techniques.