An image-domain cost function for 3-D rigid body motion estimation

We derive an image-domain cost function for calibrated 3-D rigid body motion estimation from two views. The cost function is based on the accumulation of minimum mean squared error values along the epipolar lines for a large number of small measurement windows. In comparison to other non-linear, but feature-based formulations, the minimization of this cost function does not require pre-computed point correspondences. Several speedups are derived that keep the computational complexity similar to other non-linear formulations of the 3-D rigid body motion estimation problem. The main advantage of the proposed technique is that no effort has to be devoted to the reliable determination of point correspondences.