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 …
Three-dimensional point cloud semantic segmentation for cultural heritage: a comprehensive review
S Yang, M Hou, S Li - Remote Sensing, 2023 - mdpi.com
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 …
Rpm-net: Robust point matching using learned features
Abstract Iterative Closest Point (ICP) solves the rigid point cloud registration problem
iteratively in two steps:(1) make hard assignments of spatially closest point …
iteratively in two steps:(1) make hard assignments of spatially closest point …
Evolutionary multiform optimization with two-stage bidirectional knowledge transfer strategy for point cloud registration
Point cloud registration is an important task in computer vision, where the goal is to estimate
a transformation to align a pair of point clouds. Most of the existing registration methods face …
a transformation to align a pair of point clouds. Most of the existing registration methods face …
RoReg: Pairwise point cloud registration with oriented descriptors and local rotations
We present RoReg, a novel point cloud registration framework that fully exploits oriented
descriptors and estimated local rotations in the whole registration pipeline. Previous …
descriptors and estimated local rotations in the whole registration pipeline. Previous …
You only hypothesize once: Point cloud registration with rotation-equivariant descriptors
In this paper, we propose a novel local descriptor-based framework, called You Only
Hypothesize Once (YOHO), for the registration of two unaligned point clouds. In contrast to …
Hypothesize Once (YOHO), for the registration of two unaligned point clouds. In contrast to …
Evolutionary multitasking descriptor optimization for point cloud registration
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 …
methods are widely adopted for their speed and efficiency in point cloud registration. The …
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 …
WHU-helmet: a helmet-based multisensor SLAM dataset for the evaluation of real-time 3-D map** in large-scale GNSS-denied environments
Real-time 3-D map** of large-scale global navigation satellite system (GNSS)-denied
environments plays an important role in forest inventory management, disaster emergency …
environments plays an important role in forest inventory management, disaster emergency …
Rcp: Recurrent closest point for point cloud
Abstract 3D motion estimation including scene flow and point cloud registration has drawn
increasing interest. Inspired by 2D flow estimation, recent methods employ deep neural …
increasing interest. Inspired by 2D flow estimation, recent methods employ deep neural …