Model-Based Hand Tracking Using an Unscented Kalman Filter

Abstract

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 ray tracing 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.