Fitting Globally Stabilized Algebraic Surfaces to Range Data
T. Sahin, M. Unel
Proceedings of the 10th IEEE International Conference on Computer Vision (ICCV'05)
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.