A new efficient EM-ICP algorithm for non-linear registration of 3D point sets
Year: 2012
Type: article
Abstract: In this paper, we present a new method for non-linear pairwise registration of point sets. In this method, we consider the points of the first set as the draws of a Gaussian mixture model whose centres are the points of the second set displaced by a deformation. Next we perform {\it maximum a posteriori} estimation of the parameters (which include the unknown transformation) of this model using the expectation-maximisation algorithm. Compared to other methods using the same ''EM-ICP'' paradigm/framework, we propose three key modifications leading to an efficient algorithm allowing for fast registration of large point sets: 1) symmetrisation of the point-to-point correspondences; 2) specification of priors on these correspondences using differential geometry; 3) efficient encoding of deformations using the RKHS theory and the Fourier analysis. The resulting algorithm is efficient and is able to register large data sets. We evaluate the added value of the modifications and compare our method to the state-of-the-art CPD algorithm on synthetic data.
Authors: Benoit Combès, Sylvain Prima
Institution: Empenn
Language: English
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W2556171905