Using Real-time Stereo Matching for Human Gesture Detection and Tracking
Sungil Kang · TECHART Journal of Arts and Imaging Science · 2014
This paper presents a human gesture detection and tracking system using real-time stereo matching. A disparity map is obtained from stereo matching based on general-purpose computing of graphics processing units in real-time, and then, 3-D foreground blobs are generated using depth information gathered from the map. The distribution of the 3-D foreground blobs, combined with detection of the face and torso, is applied to determine the position of the human body. A skeleton model for the upper body is successively fitted to a median axis in the area that has more 3-D blobs from the shoulder area to the hands. The position and color information obtained from the 3-D blobs for a robust tracking of arm and hand gestures are examined. The reconstructed trajectory is then classified into one of eight gesture reference sets.