Open AccessPoint cloud and BIM model registration based on genetic algorithm and ICP algorithm
Author(s) -
Chun Liu,
Meijing Guang,
Shanshan Yu
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/2132/1/012007
Subject(s) - point cloud , laser scanning , algorithm , computer science , genetic algorithm , iterative closest point , cloud computing , upsampling , data mining , 3d scanning , point (geometry) , artificial intelligence , machine learning , image (mathematics) , mathematics , laser , physics , geometry , optics , operating system
With the rapid development of the construction industry, BIM technology, and 3D laser scanning technology are being used more and more widely, and there are many applications of combining BIM technology with 3D laser scanning technology, such as quality inspection, progress inspection, or digital preservation of ancient buildings. Therefore, this paper proposes a 3D point cloud and BIM model registration scheme based on genetic algorithm and ICP algorithm, firstly, the point cloud data is pre-processed by statistical denoising method for denoising and downsampling, and the BIM model data is converted to format data; then the coarse registration is performed by genetic algorithm, and the accurate registration is performed by ICP algorithm based on KD-tree, and finally, we experimentally verify the feasibility of the algorithm in this paper, and compared with the ICP algorithm, the registration efficiency and accuracy of the algorithm in this paper are greatly improved.