Towards 3D hand tracking using a deformable model

Abstract

In this paper we first describe how we have constructed a 3D deformable Point Distribution Model of the human hand, capturing training data semi-automatically from volume images via a physically-based model. We then show how we have attempted to use this model in tracking an unmarked hand moving with 6 degrees of freedom (plus deformation) in real time using a single video camera. In the course of this we show how to improve on a weighted least-squares pose parameter approximation at little computational cost. We note the successes and shortcomings of our system and discuss how it might be improved.