Generalized least squares multiple 3D surface matching

Abstract

A method for the simultaneous co-registration and georeferencing of multiple 3D pointclouds and associated intensity information is proposed.It is a generalization of the 3D surface matching problem.The simultaneous co-registration provides for a strict solution to the problem, as opposed to sequential pairwise registration.The problem is formulated as the Least Squares matching of overlapping 3D surfaces.The parameters of 3D transformations of multiple surfaces are simultaneously estimated, using the Generalized Gauss-Markoff model, minimizing the sum of squares of the Euclidean distances among the surfaces.An observation equation is written for each surface-to-surface correspondence.Each overlapping surface pair contributes a group of observation equations to the design matrix.The parameters are introduced into the system as stochastic variables, as a second type of (fictitious) observations.This extension allows to control the estimated parameters.Intensity information is introduced into the system in the form of quasisurfaces as the third type of observations.Reference points, defining an external (object) coordinate system, which are imaged in additional intensity images, or can be located in the pointcloud, serve as the fourth type of observations.They transform the whole block of "models" to a unique reference system.Furthermore, the given coordinate values of the control points are treated as observations.This gives the fifth type of observations.The total system is solved by applying the Least Squares technique, provided that sufficiently good initial values for the transformation parameters are given.This method can be applied to data sets generated from aerial as well as terrestrial laser scanning or other pointcloud generating methods.