|Department of Engineering|
|University of Cambridge > Engineering Department > Machine Intelligence Lab|
MODEL-BASED HAND TRACKING USING AN UNSCENTED KALMAN FILTER
B.Stenger, P.R.S. Mendonça and R. Cipolla
This paper presents a novel method for hand tracking. It uses a 3D model built from quadrics which approximates the anatomy of a human hand. This approach allows for the use of results from projective geometry that yield an elegant technique to generate the projection of the model as a set of conics, as well as providing an efficient algorithm to handle self-occlusion. Once the model is projected, an Unscented Kalman Filter is used to update its pose in order to minimise the geometric error between the model projection and a video sequence on the background. Results from experiments with real data show the accuracy of the technique.
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2005 Cambridge University Engineering Dept
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