Real-time 3D pose and correspondence from stereo image sequences by combinatorial optimization

In this paper we propose a new solution to the problem of model-based pose estimation and pose tracking, using a sequence of stereo images in which a small number of landmarks are detected on the object of interest. The landmarks are reconstructed in 3D and then the simultaneous pose and correspondence problem is solved with a novel algorithm, PC-SCO, based on stochastic combinatorial optimization. We also use a new algorithm, quaternion-based characteristic polynomial (QCP), which significantly speeds up the quaternion method used in pose alignment, making possible the tracking to be done in real-time.