Sparse point cloud registration and aggregation with mesh‐based generalized iterative closest point

2021 ◽  
Author(s):  
Matthew Young ◽  
Chris Pretty ◽  
Josh McCulloch ◽  
Richard Green
Keyword(s):  
Point Cloud ◽  
Iterative Closest Point ◽  
Point Cloud Registration

Point cloud registration based on improved iterative closest point method

2012 ◽  
Vol 20 (9) ◽  
pp. 2068-2076 ◽  
Author(s):  
王欣 WANG Xin ◽  
张明明 ZHANG Ming-ming ◽  
于晓 YU Xiao ◽  
章明朝 ZHANG Ming-chao
Keyword(s):  
Point Cloud ◽  
Point Method ◽  
Iterative Closest Point ◽  
Point Cloud Registration ◽  
Closest Point Method

scholarly journals A Modified Iterative Closest Point Algorithm for 3D Point Cloud Registration

2016 ◽  
Vol 31 (7) ◽  
pp. 515-534 ◽  
Author(s):  
Roberto Marani ◽  
Vito Renò ◽  
Massimiliano Nitti ◽  
Tiziana D'Orazio ◽  
Ettore Stella
Keyword(s):  
Point Cloud ◽  
Iterative Closest Point ◽  
3D Point Cloud ◽  
Point Cloud Registration ◽  
Iterative Closest Point Algorithm

scholarly journals POINT CLOUD REGISTRATION AND ACCURACY FOR 3D MODELLING - A REVIEW

2021 ◽  
Vol 6 (24) ◽  
pp. 131-138
Author(s):  
Ahmad Firdaus Razali ◽  
Mohd Farid Mohd Ariff ◽  
Zulkepli Majid
Keyword(s):  
Feature Extraction ◽  
Point Cloud ◽  
Laser Scanning ◽  
Terrestrial Laser Scanning ◽  
3D Modelling ◽  
Iterative Closest Point ◽  
Data Types ◽  
Point Cloud Registration ◽  
Impressive Result ◽  
Mapping Point

Geoinformation is a surveying and mapping field where topography and details on the ground are spatially mapped. The point cloud is one of the data types that is used for measurement and visualisation of Earth features mapping. Point cloud could come from a different source such as terrestrial laser scanned or photogrammetry. The concepts of terrestrial laser scanning and photogrammetry surveying are elaborated in this paper. This paper also presents the method used for point cloud registration; Iterative Closest Point (ICP) and Feature Extraction and Matching (FEM) and the accuracy of laser scanned, and photogrammetric point cloud based on the previous experiments. Experimental analysis conducted in the previous study shows an impressive result on laser scanned point cloud with very mínimum errors compared to photogrammetric point cloud.

scholarly journals CICP: Cluster Iterative Closest Point for sparse–dense point cloud registration

2018 ◽  
Vol 108 ◽  
pp. 66-86 ◽  
Author(s):  
M. Lamine Tazir ◽  
Tawsif Gokhool ◽  
Paul Checchin ◽  
Laurent Malaterre ◽  
Laurent Trassoudaine
Keyword(s):  
Point Cloud ◽  
Iterative Closest Point ◽  
Point Cloud Registration ◽  
Dense Point

Point Cloud Registration Algorithm Combined Gaussian Mixture Model and Point-to-Plane Metric

2018 ◽  
Vol 30 (4) ◽  
pp. 642
Author(s):  
Guichao Lin ◽  
Yunchao Tang ◽  
Xiangjun Zou ◽  
Qing Zhang ◽  
Xiaojie Shi ◽  
...  
Keyword(s):  
Gaussian Mixture Model ◽  
Mixture Model ◽  
Point Cloud ◽  
Gaussian Mixture ◽  
Point Cloud Registration ◽  
Registration Algorithm

scholarly journals Graphite: Graph-Induced Feature Extraction for Point Cloud Registration

2020 ◽  
Author(s):  
Mahdi Saleh ◽  
Shervin Dehghani ◽  
Benjamin Busam ◽  
Nassir Navab ◽  
Federico Tombari
Keyword(s):  
Feature Extraction ◽  
Point Cloud ◽  
Point Cloud Registration
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