vision-based two hand detection and tracking
In the field of human computer interaction (HCI), hand has been widely used as input device for natural interaction. However, during hand tracking, the continuously changing of hand shape and the interference from distractors (faces or hands) or occlusion reduce the robustness of man-machine alternation. In this paper, we use a web camera to detect two hands automatically and then track them stably in order to go against the problems mentioned above. At the first stage, we put forward a contour-based method to extract five fingertips which provide cues to locate initial hand position. At the second stage, CamShift is adopted to track the located hands. However, the means may easily lose the tracked objects due to its inadaptability to distractors and occlusion. Hence, we employ an improved Grey Model which is a good predictor of historical data to guide CamShift so as to achieve more accurate tracking. Experiments have been divided into two groups including the distractors tests and the occlusion tests. The convincing results illustrate the effectiveness of the proposed algorithm.
hand detection and tracking camshift grey model