3D Camera Tracking in Unknown Environments by On-line Keypoint Learning

In this paper we present an efficient algorithm for camera tracking applicable for mobile devices. In particular, the work is motivated by the limited computational power and memory, precluding the use of existing methods for estimation of the 6-DoF pose of a mobile device (camera) relative to a previously unknown planar object. Similar to existing methods, we introduce a keypoint based approach. We establish a relationship between the object and its image by selecting keypoints on the object, preferably such with a distinctive appearance, and identifying their location within subsequent images. In contrast to existing works, we solve the problem of re-identifying such feature points by robustly learning their appearance with an on-line learning algorithm. We demonstrate the proposed algorithm, hence not limited to this application, in the context of AR. In particular, we give several qualitative and quantitative evaluations showing the benefits of the proposed approach.