Point cloud collection forming a 3D scene typically uses information from multiple data
scans. The common approach is to register the point cloud pairs consequentially using a …

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 …

The problem of aligning of 3D point data is the known registration task. The most popular
registration algorithm is the Iterative Closest Point (ICP). This paper proposes a new …

We propose a robust registration method for two point sets using Lie group parametrization.
Our algorithm is termed as LieTrICP, as it combines the advantages of the Trimmed Iterative …

Robust point set registration is a challenging problem, especially in the cases of noise,
outliers, and partial overlap**. Previous methods generally formulate their objective …

The registration of point clouds in a three-dimensional space is an important task in many
areas of computer vision, including robotics and autonomous driving. The purpose of …

The most popular algorithm for aligning of three‐dimensional point data is the iterative
closest point (ICP). In this paper, a new algorithm for orthogonal registration of point clouds …

Image registration is a fundamental medical image analysis task. Ideally, registration should
focus on aligning semantically corresponding voxels, ie, the same anatomical locations …

In medical imaging studies, there is an increasing trend for discovering the intrinsic
anatomical difference across individual subjects in a dataset, such as hand images for …

The problem of aligning of 3D point data is the known registration task. The most popular
registration algorithm is the Iterative Closest Point (ICP) algorithm. The traditional ICP …