An improved ICP registration algorithm with a weight-bootstrap scheme

In this paper, we propose a variant of the iterative closet point (ICP) registration method by introducing a novel weight-bootstrap scheme. The rigid transform between two point sets can be estimated, as long as proper correspondences are given. The accuracy of the estimated transform is mainly determined by the goodness of these matches. However, the confidence of the correspondences is weakened by the observation error. Aiming to address this challenge, the proposed solution parameterizes the pair matching confidence and improves the optimization process. Specifically, we adopt the tangent distance as error metric and introduce an iterative bootstrapped quadratic approximation method to increase the registration accuracy. Compared to the existing methods, experiments show that our method can produce a more accurate transform estimation in 2D case, and yield an acceptable result in 3D case.