Structural ICP algorithm for pose estimation based on local features

In this paper we present a new variant of the ICP (iterative closest point) algorithm for finding correspondences between image and model points. This new variant uses structural information from the model points and contour segments detected in images to find better conditioned correspondence sets and to use them to compute the 3D pose. A local representation of 3D free-form contours is used to get the structural information in 3D space and in the image plane. Furthermore, the local structure of free-form contours is combined with orientation and phase as local features obtained from the monogenic signal. With this combination, we achieve a more robust correspondence search. Our approach was tested on synthetical and real data to compare the convergence and performance of our approach against the classical ICP approach.