Matching and motion estimation of three-dimensional point and line sets using eigenstructure without correspondences

This paper presents moment-based algorithms for matching and motion estimation of three-dimensional (3D) point or line sets without correspondences and application of these algorithms to object tracking over long image sequences. The motion analysis is performed by identifying two sets of coordinate directions based on the relative position of points (or lines) before and after the motion. Since these coordinate vectors are motion invariant, the relationship between them gives parameters of rigid motion. However, we need to determine the set matching before and after the motion estimation algorithms can be applied. We propose several measures suitable for matching of 3D point (and line) sets. We also evaluate these approaches with simulated data and develop criteria for determining the sensitivity to noise. Finally, we apply the proposed algorithm to a time sequence of experimental data (moving vehicle) on which 3D points were determined by stereo matching.