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Robust Generalized Total Least Squares Iterative Closest Point RegistrationR. San Jose Estepar, A. Brun, C.-F. WestinSeventh International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI'04) Pages 234-241 September, 2004 AbstractThis paper investigates the use of a total least squares approach in a generalization of the iterative closest point (ICP) algorithm for shape registration. A new Generalized Total Least Squares (GTLS) formulation of the minimization process is presented opposed to the traditional Least Squares (LS) technique. Accounting for uncertainty both in the target and in the source models will lead to a more robust estimation of the transformation. Robustness against outliers is guaranteed by an iterative scheme to update the noise covariances. Experimental results show that this generalization is superior to the least squares counterpart.
ReferenceSan Jose Estepar R, Brun A, Westin CF. Robust generalized total least squares iterative closest point registration. In Seventh International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI'04), Lecture Notes in Computer Science. Rennes - Saint Malo, France, 2004;234-241.Bibtex entry
@InProceedings{san-joseMICCAI04,
author = {R. {San Jose Estepar} and A. Brun and C.-F. Westin},
title = {Robust Generalized Total Least Squares Iterative Closest
Point Registration},
booktitle = {Seventh International Conference on Medical Image Computing
and Computer-Assisted Intervention (MICCAI'04)},
series = {Lecture Notes in Computer Science},
pages = {234-241},
year = {2004},
address = {Rennes - Saint Malo, France},
month = {September}
}
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