Multiple view surface registration with error modeling and analysis

We describe a new 3D surface rigid registration system which allows the assignment of individual measurement error models to each surface point. Any number of surfaces may be registered simultaneously. The error models are used in the registration to compute statistically optimal registration parameters, as well as to estimate the error covariance of those parameters. Previous surface registration techniques have implicitly assumed an isotropic Gaussian measurement error distribution for all points. However, that does not reflect the nature of non-contact 3D surface measurements, whose error characteristics are often strongly directional