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Occlusion-Free Hand Motion Tracking by Multiple Cameras and Particle Filtering with Prediction


Makoto Kato, Gang Xu


Vol. 6  No. 10  pp. 58-65


This paper proposes a new technique to simultaneously estimate the global hand pose and the finger articulation imaged by multiple cameras. Tracking a free hand motion against a cluttered background is a difficult task. The first reason is that hand fingers are self-occluding and the second reason is the high dimensionality of the problem. In order to solve these difficulties, we propose using calibrated multiple cameras and at the same time improving search efficiency by predicted particle filtering. Therefore our methods can cope with both rapid global hand motion and self-occlusion. We also add prediction to particle filtering so that more particles are generated in areas of higher likelihood, which reduces search cost significantly. The effectiveness of our method is demonstrated by tracking free hand motions in real image sequences


Articulated hand tracking, Motion, Gesture recognition, Particle filtering, Motion capture