A tutorial review on point cloud registrations: principle, classification, comparison, and technology challenges
A point cloud as a collection of points is poised to bring about a revolution in acquiring and
generating three‐dimensional (3D) surface information of an object in 3D reconstruction …
generating three‐dimensional (3D) surface information of an object in 3D reconstruction …
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 …
[HTML][HTML] How to make sense of 3D representations for plant phenotyping: a compendium of processing and analysis techniques
N Harandi, B Vandenberghe, J Vankerschaver… - Plant Methods, 2023 - Springer
Computer vision technology is moving more and more towards a three-dimensional
approach, and plant phenotyping is following this trend. However, despite its potential, the …
approach, and plant phenotyping is following this trend. However, despite its potential, the …
Point set registration: Coherent point drift
A Myronenko, X Song - IEEE transactions on pattern analysis …, 2010 - ieeexplore.ieee.org
Point set registration is a key component in many computer vision tasks. The goal of point
set registration is to assign correspondences between two sets of points and to recover the …
set registration is to assign correspondences between two sets of points and to recover the …
Robust point set registration using gaussian mixture models
In this paper, we present a unified framework for the rigid and nonrigid point set registration
problem in the presence of significant amounts of noise and outliers. The key idea of this …
problem in the presence of significant amounts of noise and outliers. The key idea of this …
[图书][B] Statistical shape analysis: with applications in R
A thoroughly revised and updated edition of this introduction to modern statistical methods
for shape analysis Shape analysis is an important tool in the many disciplines where objects …
for shape analysis Shape analysis is an important tool in the many disciplines where objects …
A Bayesian formulation of coherent point drift
O Hirose - IEEE transactions on pattern analysis and machine …, 2020 - ieeexplore.ieee.org
Coherent point drift is a well-known algorithm for solving point set registration problems, ie,
finding corresponding points between shapes represented as point sets. Despite its …
finding corresponding points between shapes represented as point sets. Despite its …
Multi-scale EM-ICP: A fast and robust approach for surface registration
S Granger, X Pennec - Computer Vision—ECCV 2002: 7th European …, 2002 - Springer
We investigate in this article the rigid registration of large sets of points, generally sampled
from surfaces. We formulate this problem as a general Maximum-Likelihood (ML) estimation …
from surfaces. We formulate this problem as a general Maximum-Likelihood (ML) estimation …
Non-rigid point set registration: Coherent point drift
A Myronenko, X Song… - Advances in neural …, 2006 - proceedings.neurips.cc
Abstract We introduce Coherent Point Drift (CPD), a novel probabilistic method for nonrigid
registration of point sets. The registration is treated as a Maximum Likelihood (ML) …
registration of point sets. The registration is treated as a Maximum Likelihood (ML) …
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 …