Recently, the advancement of deep learning (DL) in discriminative feature learning from 3-D
LiDAR data has led to rapid development in the field of autonomous driving. However …

A point cloud is a set of points defined in a 3D metric space. Point clouds have become one
of the most significant data formats for 3D representation and are gaining increased …

Over recent decades, 3D point clouds have been a popular data source applied in automatic
change detection in a wide variety of applications. Compared with 2D images, using 3D …

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 …

Laser scanning can provide timely assessments of mine sites despite adverse challenges in
the operational environment. Although there are several published articles on laser …

In the cultural heritage field, point clouds, as important raw data of geomatics, are not only
three-dimensional (3D) spatial presentations of 3D objects but they also have the potential …

Point cloud registration is an important task for other point cloud tasks. Feature-based
methods are widely adopted for their speed and efficiency in point cloud registration. The …

Point cloud registration (PCR) is an important task in photogrammetry and remote sensing,
whose goal is to seek a seven-parameter similarity transformation to register a pair of point …

Nowadays, point clouds acquired through laser scanning and stereo matching have
deemed to be one of the best sources for map** urban scenes. Spatial coordinates of 3-D …

Although significant improvement has been achieved in fully autonomous driving and
semantic high-definition map (HD) domains, most of the existing 3D point cloud …