In this paper we present a natural feature tracking algorithm based on on-line boosting used for localizing a mobile computer. Mobile augmented reality requires highly accurate and fast six degrees of freedom tracking in order to provide registered graphical overlays to a mobile user. With advances in mobile computer hardware, vision-based tracking approaches have the potential to provide efficient solutions that are non-invasive in contrast to the currently dominating marker-based approaches. We propose to use a tracking approach which can use in an unknown environment, i.e. the target has not be known beforehand. The core of the tracker is an on-line learning algorithm, which updates the tracker as new data becomes available. This is suitable in many mobile augmented reality applications. We demonstrate the applicability of our approach on tasks where the target objects are not known beforehand, i.e. interactive planing.
['Gerhard Schall', 'Helmut Grabner', 'Michael Grabner', 'Paul Wohlhart', 'Dieter Schmalstieg', 'Horst Bischof']
3D tracking in unknown environments using on-line keypoint learning for mobile augmented reality