Abstract
Researchers have successfully recognized specific fingers of the hand by silhouette images and distinguished a small set of hand signs by contour features of images. However, the silhouette or contour features recovered from the images do not provide sufficient information to generate a 3D hand posture with the fingers positioned properly. This failure led to our study, which developed a new method employing a hand model that can automatically analyze 3D hand postures using static stereo images. Guided by internal constraints and external forces, the model is automatically fitted to the hand image. Our method differs from previous methods in that it captures 27 interacting hand parameters, including finger joint angles, enabling suitable reconstruction of 3D hand posture. >
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