DYNAMIC HAND GESTURE RECOGNITION; REAL TIME VS. OFFLINE RECOGNITION USING KINECT
As a part of natural interfaces, the sign language recognition (SLR) is considered an important area of research. This work describes two dynamic SLR systems based on two different methods, real time (online) and offline ones. We used the Microsoft Kinect camera in this task. We developed these methods for three different gestures; waving, pushing and circular. A comparison between the two methods has been performed. We found that the recognition rate for the online hand gesture recognition is lower than the recognition rate for the offline one. They are 89% and 100%, respectively.
real time hand gesture recognition, offline hand gesture recognition, hidden Markov model, Kinect based recognition.