Aligning indoor and outdoor point clouds is a challenging problem since the overlapping
area is usually limited, thus resulting in a lack of correspondence features. The windows and …

Current point cloud registration methods are mainly based on local geometric information
and usually ignore the semantic information contained in the scenes. In this article, we treat …

Remote sensing image registration can benefit from a machine learning method based on
the likelihood of predicting semantic spatial position distributions. Semantic segmentation of …

Most existing correspondence-free registration methods suffer from performance
degradation in partial overlapped point clouds. To solve the partial overlapped point cloud …

RegHEC is a registration-based hand-eye calibration technique with no need for accurate
calibration rig but arbitrary available objects, applicable for both eye-in-hand and eye-to …

In consideration of the significant changes in urban environmental scenes and the impact of
factors such as signal obstruction on positioning, the spatial positions of multi-temporal …

The registration of multiple local maps is a crucial step in multi-robot collaboration. However,
existing methods are insufficient to address the complexities associated with sparse features …

The establishment of point‐to‐point correspondence between point clouds is called three‐
dimensional point matching, which is widely used in computer vision, computer graphics …

Since the geometric transformation relationship of similar surfaces with complex features,
such as local deformation and curvature changes, is hard to be solved through global …

Abstract 3D rigid point cloud registration dedicates to estimating rotation and translation that
register point clouds, potentially partially overlapped, into a coherent coordinate system …