Iterative Procrustes alignment with the EM algorithm

B. Luo, E.R. Hancock
2002 Image and Vision Computing  
This paper casts the problem of point-set alignment via Procrustes analysis into a maximum likelihood framework using the EM algorithm. The aim is to improve the robustness of the Procrustes alignment to noise and clutter. By constructing a Gaussian mixture model over the missing correspondences between individual points, we show how alignment can be realised by applying singular value decomposition to a weighted point correlation matrix. Moreover, by gauging the relational consistency of the
more » ... signed correspondence matches, we can edit the point sets to remove clutter. The method can be used to match unlabelled point-sets of different size. We illustrate the effectiveness of the method matching stereograms. We also provide a sensitivity analysis to demonstrate the operational advantages of the method. q
doi:10.1016/s0262-8856(02)00010-0 fatcat:gmyy2ca2ynaizkds54t227jehi