GraphTracker: a topology projection invariant optical tracker

In this paper, we describe a new optical tracking algorithm for pose estimation of interaction devices in virtual and augmented reality. Given a 3D model of the interaction device and a number of camera images, the primary difficulty in pose reconstruction is to find the correspondence between 2D image points and 3D model points. Most previous methods solved this problem by the use of stereo correspondence. Once the correspondence problem has been solved, the pose can be estimated by determining the transformation between the 3D point cloud and the model. Our approach is based on the projective invariant topology of graph structures. The topology of a graph structure does not change under projection: in this way we solve the point correspondence problem by a subgraph matching algorithm between the detected 2D image graph and the model graph. There are four advantages to our method. First, the correspondence problem is solved entirely in 2D and therefore no stereo correspondence is needed. Consequently, we can use any number of cameras, including a single camera. Secondly, as opposed to stereo methods, we do not need to detect the same model point in two different cameras, and therefore our method is much more robust against occlusion. Thirdly, the subgraph matching algorithm can still detect a match even when parts of the graph are occluded, for example by the users hands. This also provides more robustness against occlusion. Finally, the error made in the pose estimation is significantly reduced as the amount of cameras is increased.