Deep learning for lidar point clouds in autonomous driving: A review
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 …
LiDAR data has led to rapid development in the field of autonomous driving. However …
[HTML][HTML] Deep learning on 3D point clouds
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 …
of the most significant data formats for 3D representation and are gaining increased …
Registration of large-scale terrestrial laser scanner point clouds: A review and benchmark
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 …
scanner (TLS) point cloud registration methods and a better understanding of their strengths …
[HTML][HTML] Change detection of urban objects using 3D point clouds: A review
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 …
change detection in a wide variety of applications. Compared with 2D images, using 3D …
[HTML][HTML] A review of laser scanning for geological and geotechnical applications in underground mining
Laser scanning can provide timely assessments of mine sites despite adverse challenges in
the operational environment. Although there are several published articles on laser …
the operational environment. Although there are several published articles on laser …
[HTML][HTML] Three-dimensional point cloud semantic segmentation for cultural heritage: a comprehensive review
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 …
three-dimensional (3D) spatial presentations of 3D objects but they also have the potential …
Point cloud registration based on one-point ransac and scale-annealing biweight estimation
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 …
whose goal is to seek a seven-parameter similarity transformation to register a pair of point …
Multi-scale point-wise convolutional neural networks for 3D object segmentation from LiDAR point clouds in large-scale environments
Although significant improvement has been achieved in fully autonomous driving and
semantic high-definition map (HD) domains, most of the existing 3D point cloud …
semantic high-definition map (HD) domains, most of the existing 3D point cloud …
Toward building and civil infrastructure reconstruction from point clouds: A review on data and key techniques
Nowadays, point clouds acquired through laser scanning and stereo matching have
deemed to be one of the best sources for mapping urban scenes. Spatial coordinates of 3-D …
deemed to be one of the best sources for mapping urban scenes. Spatial coordinates of 3-D …
Pairwise coarse registration of point clouds in urban scenes using voxel-based 4-planes congruent sets
To ensure complete coverage when measuring a large-scale urban area, pairwise
registration between point clouds acquired via terrestrial laser scanning or stereo image …
registration between point clouds acquired via terrestrial laser scanning or stereo image …