This study had two main aims:(1) to provide a comprehensive review of terrestrial laser
scanner (TLS) point cloud registration methods and a better understanding of their strengths …

As a fundamental and critical task in various visual applications, image matching can identify
then correspond the same or similar structure/content from two or more images. Over the …

This paper presents a comprehensive literature review on point set registration. The state-of-
the-art modeling methods and algorithms for point set registration are discussed and …

Point cloud registration is a fundamental problem in 3D computer vision, graphics and
robotics. For the last few decades, existing registration algorithms have struggled in …

We present a fast feature-metric point cloud registration framework, which enforces the
optimisation of registration by minimising a feature-metric projection error without …

Deep point cloud registration methods face challenges to partial overlaps and rely on
labeled data. To address these issues, we propose UDPReg, an unsupervised deep …

Multi-view point cloud registration is fundamental in 3D reconstruction. Since there are close
connections between point clouds captured from different viewpoints, registration …

In the Kalman filter (KF), the estimated state is a linear combination of the one-step
prediction and measurement. The two combination weights depend on the prediction mean …

Probabilistic 3D point cloud registration methods have shown competitive performance in
overcoming noise, outliers, and density variations. However, registering point cloud pairs in …

Point cloud registration sits at the core of many important and challenging 3D perception
problems including autonomous navigation, SLAM, object/scene recognition, and …