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This paper investigates the use of a total least squares ap- proach 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 tra- ditional Least Squares (LS) technique. Accounting for uncertainty both in the target and in the source models will lead to a more robust estima- tion 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.

Robust Generalized Total Least Squares Iterative Closest Point Registration