Hand Gesture Recognition Based on Depth Image Using Kinect Sensor

Hand gesture is becoming one of the most common ways that people use in information technology products needing interaction between people and computer, which brings to user an interesting experience. 3D camera are developed recently, e.g. Kinect, not only provide color image, but also depth map. It opens a new opportunity in development of human computer interaction (HCI) application. This paper shows a novel hand gesture recognition method based on depth image obtained from the Kinect sensor. Firstly, the hand region extraction is done by putting thresholds on hand point detected by using NITE 2 library provided by PrimeSense. Secondly, we extract the feature vector including the number of open fingers, the angles between the fingertips and horizontal of the hand, the angles between two consecutive fingers, and the difference between the distance from the hand center to the fingertips and the radius of the biggest inscribed circle. Finally, a support vector machine (SVM) is applied to identify different gestures. The experimental result shows that the proposed method performs hand gesture recognition at accuracy of 95% in real-time.