Indoor mapping using low-cost MLS point clouds and architectural skeleton constraints-Reference-Cited by-同舟云学术

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Indoor mapping using low-cost MLS point clouds and architectural skeleton constraints

Published:2023-06 Issue: Volume:150 Page:104837
ISSN:0926-5805
Container-title:Automation in Construction
language:en
Short-container-title:Automation in Construction

Author:

Luo Junqi,Ye Qin,Zhang Shaoming,Yang Zexin

Funder

Natural Science Foundation of Shanghai

National Natural Science Foundation of China

Publisher

Elsevier BV

Subject

Building and Construction,Civil and Structural Engineering,Control and Systems Engineering

Reference66 articles.

1. Immersive virtual reality for extending the potential of building information modeling in architecture, engineering, and construction sector: systematic review;Safikhani;Int. J. Digit. Earth,2022

2. Automatic region-growing system for the segmentation of large point clouds;Poux;Autom. Constr.,2022

3. Automatic voxel-based 3D indoor reconstruction and room partitioning from triangle meshes;Hubner;ISPRS J. Photogramm. Remote Sens.,2021

4. Multi-sensor platform for indoor mobile mapping: system calibration and using a total station for indoor applications;Keller;Remote Sens.,2013

5. A simple information fusion method provides the obstacle with saliency labeling as a landmark in robotic mapping;Hu;Alex. Eng. J.,2022

Cited by 4 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Point cloud registration considering safety nets during scaffold installation using sensor fusion and deep learning;Automation in Construction;2024-03

2. Benchmarking Deep Learning Architectures for Urban Vegetation Point Cloud Semantic Segmentation From MLS;IEEE Transactions on Geoscience and Remote Sensing;2024

3. Coarse Alignment Methodology of Point Cloud Based on Camera Position/Orientation Estimation Model;Journal of Imaging;2023-12-14

4. 3D Visual Reconstruction as Prior Information for First Responder Localization and Visualization;Sensors;2023-09-10

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