Journal Article

A regularized point cloud registration approach for orthogonal transformations

Voronin, Sergei, Makovetskii, Artyom, Kober, Vitaly, Voronin, Aleksei

2022

Overview

An important part of the well-known iterative closest point algorithm (ICP) is the variational problem. Several variants of the variational problem are known, such as point-to-point, point-to-plane, generalized ICP, and normal ICP (NICP). This paper proposes a closed-form exact solution for orthogonal registration of point clouds based on the generalized point-to-point ICP algorithm. We use points and normal vectors to align 3D point clouds, while the common point-to-point approach uses only the coordinates of points. The paper also presents a closed-form approximate solution to the variational problem of the NICP. In addition, the paper introduces a regularization approach and proposes reliable algorithms for solving variational problems using closed-form solutions. The performance of the algorithms is compared with that of common algorithms for solving variational problems of the ICP algorithm. The proposed paper is significantly extended version of Makovetskii et al. (CCIS 1090, 217–231, 2019).

• Publisher: Springer Nature B.V
• Subject: Algorithms / Approximation / Closed form solutions / Correspondence / Exact solutions / Iterative algorithms / Mathematical analysis / Methods / Optimization / Registration / Regularization / Three dimensional models