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Iterative Procrustes alignment with the EM algorithm
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
doi:10.1016/s0262-8856(02)00010-0
fatcat:gmyy2ca2ynaizkds54t227jehi