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Fitting Globally Stabilized Algebraic Surfaces to Range Data
Authors: T. Sahin, M. Unel
Published in: Proceedings of the 10th IEEE International Conference on Computer Vision (ICCV'05)
Publication year: 2005
Abstract: Linear fitting of implicit algebraic models to data usually suffers from global stability problems. Complicated object structures can accurately be modeled by closed-bounded surfaces of higher degrees using ridge regression. This paper derives an explicit formula for computing a Euclidean invariant 3D ridge regression matrix and applies it for the global stabilization of a particular linear fitting method. Experiments show that the proposed approach improves global stability of resulting surfaces significantly.
 

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