Finger identification and hand gesture recognition techniques for natural user interface

Abstract

The natural user interface using hand gesture have been popular field in Human-Computer-Interaction(HCI). Many research papers have been proposed in this field. They proposed vision-based, glove-based and depth-based approach for hand gesture recognition. However, hand gesture itself is simple and not natural way to interact. In otherwise, hand gesture recognition using finger tracking and identification can be implemented more robust and subtle recognition. Recently, new horizons are open with the development of sensors and technology such as Kinect and Depth-Sense. This development has made possible robust recognition, like finger identification and hand gesture recognition in bad conditions such as dark light and rough background as well. In this paper, we proposed a new finger identification and hand gesture recognition techniques with kinect depth data. Our proposed finger identification and gesture recognition methods provide natural interactions and interface by using fingers. We implemented interfaces and designed hand gestures using this method. This paper explains finger identification method and hand gesture recognition in detail. We show the preliminary experiment for evaluating accuracy of finger identification and hand gesture recognition accuracy. Finally, we discuss the result of evaluation and our contributions.