@inproceedings{52a1e2ead99f48b3a7d867cdcd007f51,
title = "Non-rigid point set registration: Coherent Point Drift",
abstract = "We introduce Coherent Point Drift (CPD), a novel probabilistic method for nonrigid registration of point sets. The registration is treated as a Maximum Likelihood (ML) estimation problem with motion coherence constraint over the velocity field such that one point set moves coherently to align with the second set. We formulate the motion coherence constraint and derive a solution of regularized ML estimation through the variational approach, which leads to an elegant kernel form. We also derive the EM algorithm for the penalized ML optimization with deterministic annealing. The CPD method simultaneously finds both the non-rigid transformation and the correspondence between two point sets without making any prior assumption of the transformation model except that of motion coherence. This method can estimate complex non-linear non-rigid transformations, and is shown to be accurate on 2D and 3D examples and robust in the presence of outliers and missing points.",
author = "Andriy Myronenko and Xubo Song and Miguel Carreira-Perpi{\~n}{\'a}n",
note = "Publisher Copyright: {\textcopyright} NIPS 2006.All rights reserved; 19th International Conference on Neural Information Processing Systems, NIPS 2006 ; Conference date: 04-12-2006 Through 07-12-2006",
year = "2006",
language = "English (US)",
series = "NIPS 2006: Proceedings of the 19th International Conference on Neural Information Processing Systems",
publisher = "MIT Press Journals",
pages = "1009--1016",
editor = "Bernhard Scholkopf and Platt, {John C.} and Thomas Hofmann",
booktitle = "NIPS 2006",
address = "United States",
}