Multi-feature gesture recognition based on Kinect

Human Computer Interaction (HCI) has been a popular research area during the last few years. Compared with the tradition HCI methods such as using a keyboard or mouse, people prefer to have their tasks done in a more natural way. As an essential form of non-verbal communication in daily life, gesture is a good choice to turn the ideas into reality. Although various recognition methods are proposed to solve the problem, these methods are time-tensed, space-tensed or miscellaneous. This paper introduced a new method to recognize the hand gesture correctly and efficiently. The recognition is done through two phases: the skeleton phase concerning capturing and processing skeleton feature of the hand gesture, and the hand phase focusing on extracting hand contour feature of the hand gesture. Experimental results confirm an overall 94% accuracy in recognizing and matching the pre-defined templates and robustness to backgrounds.