An adaptive training-free feature tracker for mobile phones

While tracking technologies based on fiducial markers have dominated the development of Augmented Reality (AR) applications for almost a decade, various real-time capable approaches to markerless tracking have recently been presented. However, most existing approaches do not yet achieve sufficient frame rates for AR on mobile phones or at least require an extensive training phase in advance. In this paper we will present our approach on feature based tracking applying robust SURF features. The implementation is more than one magnitude faster than previous ones, allowing running even on mobile phones at highly interactive rates. In contrast to other feature based approaches on mobile phones, our implementation may immediately track features captured from a photo without any training. Further, the approach is not restricted to planar surfaces, but may use features of 3D objects.