Hand gesture recognition using two differential PIR sensors and a camera

In this paper, a hand gesture detection and classification system using two differential Pyro-electric Infrared (PIR) sensors and a camera is introduced. Motion presence is investigated in the area of interest using two differential PIR sensors. In the case of any motion detection, a decision whether it belongs to a hand or not is made by using camera and if it is a hand, which gesture belongs to which predefined class is determined by evaluating each system data together. In the stage of hand gesture detection and classification using camera, skin detection and convex hull-defect algorithms are used. Classification of different hand gestures by using differential PIR sensors is carried out by Winner-Take-All (WTA) hash method. The main contribution of this paper is to show that WTA hash codes can be utilized in classification of 1-D signals and gesture recognition accuracy can be improved by multi-sensor fusion.