| dc.description.abstract | In recent year, gesture recognition is an important issue in the field of human computer interaction. The most commonly used applications include game control, home appliances control, robot control, etc. Moreover, due to the effect of lighting, complex backgrounds and the restricted standard gestures without curvature of the fingers, some gesture recognition methods systems are neither intuitive nor comfortable for users. Thus, a loose gesture recognition system against lighting and complex backgrounds is needed.
The purpose of this thesis is to develop a depth-based loose static gesture recognition system which could recognize fifteen common gestures. The proposed gesture recognition system includes two parts: hand detection and gesture recognition. In hand detection, we only capture the depth map against lighting and complex backgrounds from Kinect, and then we locate the hand region from the depth map with skeleton tracking using Kinect SDK. In gesture recognition, first, we create a signature which is a 1-D functional representation of the hand boundary. It is formed by plotting the distance from the center of palm to the hand boundary. Second, we detect features in the signature, and then we locate the Metacarpophalangeal joints of each finger from the hand region. Third, we calculate the angle of each finger by specifying three points: the center of palm at the vertex and then the anchor point and the Metacarpophalangeal joint on the rays. Finally, the system will identify each finger based on an angle table, using the number of fingers and their angles to determine the loose static gesture.
In this thesis, experiments show the accuracy is up to 95% in finger counting. In recognition accuracy, 90.03% for standard gestures, 80.24% for loose gestures, and hand shape using polygonal approximation is better than original hand shape. | en_US |