A review of point cloud registration algorithms for mobile robotics
The topic of this review is geometric registration in robotics. Registration algorithms
associate sets of data into a common coordinate system. They have been used extensively …
associate sets of data into a common coordinate system. They have been used extensively …
A review of recent range image registration methods with accuracy evaluation
The three-dimensional reconstruction of real objects is an important topic in computer vision.
Most of the acquisition systems are limited to reconstruct a partial view of the object …
Most of the acquisition systems are limited to reconstruct a partial view of the object …
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 …
Pointnetlk: Robust & efficient point cloud registration using pointnet
Y Aoki, H Goforth, RA Srivatsan… - Proceedings of the …, 2019 - openaccess.thecvf.com
PointNet has revolutionized how we think about representing point clouds. For classification
and segmentation tasks, the approach and its subsequent variants/extensions are …
and segmentation tasks, the approach and its subsequent variants/extensions are …
Omnet: Learning overlapping mask for partial-to-partial point cloud registration
Point cloud registration is a key task in many computational fields. Previous correspondence
matching based methods require the inputs to have distinctive geometric structures to fit a …
matching based methods require the inputs to have distinctive geometric structures to fit a …
Efficient variants of the ICP algorithm
S Rusinkiewicz, M Levoy - … third international conference on 3-D …, 2001 - ieeexplore.ieee.org
The ICP (Iterative Closest Point) algorithm is widely used for geometric alignment of three-
dimensional models when an initial estimate of the relative pose is known. Many variants of …
dimensional models when an initial estimate of the relative pose is known. Many variants of …
Least squares 3D surface and curve matching
The automatic co-registration of point clouds, representing 3D surfaces, is a relevant
problem in 3D modeling. This multiple registration problem can be defined as a surface …
problem in 3D modeling. This multiple registration problem can be defined as a surface …
Multiview registration for large data sets
K Pulli - Second international conference on 3-d digital imaging …, 1999 - ieeexplore.ieee.org
We present a multiview registration method for aligning range data. We first align scans
pairwise with each other and use the pairwise alignments as constraints that the multiview …
pairwise with each other and use the pairwise alignments as constraints that the multiview …
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 …
Robust registration of point sets using iteratively reweighted least squares
P Bergström, O Edlund - Computational optimization and applications, 2014 - Springer
Registration of point sets is done by finding a rotation and translation that produces a best fit
between a set of data points and a set of model points. We use robust M-estimation …
between a set of data points and a set of model points. We use robust M-estimation …