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Pairwise registration of TLS point clouds by deep multi-scale local features

  • Published:2020-04 Issue: Volume:386 Page:232-243
  • ISSN:0925-2312
  • Container-title:Neurocomputing
  • language:en
  • Short-container-title:Neurocomputing

Author:

Li Wei,Wang ChengORCID,Wen ChengluORCID,Zhang Zheng,Lin Congren,Li Jonathan

Funder

National Natural Science Foundation of China

Fujian Provincial Department of Education Science and Technology

Publisher

Elsevier BV

Subject

Artificial Intelligence,Cognitive Neuroscience,Computer Science Applications

Reference44 articles.

1. M. Lemmens, Terrestrial Laser Scanning, Springer Netherlands, Dordrecht, pp. 101–121.

2. A method for registration 3-D shapes;Besl;IEEE Trans. Pattern Anal. Mach. Intell.,1992

3. Improving ICP with easy implementation for free-form surface matching;Liu;Pattern Recognit.,2004

4. A method for automated registration of unorganised point clouds;Bae;ISPRS J. Photogramm. Remote Sens.,2008

5. Go-ICP: solving 3d registration efficiently and globally optimally;Yang,2013

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1. Local Feature Descriptor Construction Technique Based on Point Pair Features and Spatial Features and Its Quantitative Evaluation;2024 4th International Conference on Neural Networks, Information and Communication (NNICE);2024-01-19

2. A Globally Optimal Multi-Constrained Point Cloud Registration Algorithm;2023 International Conference on Advances in Electrical Engineering and Computer Applications (AEECA);2023-08-18

3. A 3D Point Cloud Model-Based Inspection Method for the Dimension of Prefabricated Steel Members;Advances in Automation, Mechanical and Design Engineering;2023

4. Robust consensus-aware network for 3D point registration;Neurocomputing;2022-12

5. Estimation of coronary artery movement using a non-rigid registration with global-local structure preservation;Computers in Biology and Medicine;2022-02
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