Laser & Optoelectronics Progress, Volume. 59, Issue 24, 2415007(2022)
High-Precision Registration of Non-Homologous Point Clouds in Laser Scanning and Photogrammetry
Fig. 1. Algorithm flow
Fig. 2. FPFH calculation principle
Fig. 3. Schematic diagram of octree structure
Fig. 4. Point cloud visualization. (a) Face point cloud; (b) ear point cloud; (c) buddha head point cloud
Fig. 5. Rough registration results of different algorithms. (a) Overall point cloud after down sampling; (b) 4PCS algorithm; (c) RANSAC algorithm; (d) proposed algorithm
Fig. 6. Iterative estimation of grid size
Fig. 7. Octree grid rendering. (a) Face point cloud; (b) ear point cloud; (c) buddha head point cloud
Fig. 8. Corresponding point matching diagrams. (a) Before removing false matching; (b) after removing false matching; (c) the number of point pairs corresponding to the removal of errors varying with the number of iterations
Fig. 9. Registration results of different methods. (a) Grid centroid; (b) nearest point of grid centroid ; (c) point with the smallest Euclidean distance in the grid
Fig. 10. Registration results of different algorithms. (a) ICP algorithm; (b) proposed algorithm
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Chunmei Hu, Huajie Fei, Guofang Xia, Xi Liu, Xinjian Ma. High-Precision Registration of Non-Homologous Point Clouds in Laser Scanning and Photogrammetry[J]. Laser & Optoelectronics Progress, 2022, 59(24): 2415007
Category: Machine Vision
Received: Aug. 12, 2022
Accepted: Oct. 9, 2022
Published Online: Nov. 30, 2022
The Author Email: Fei Huajie (979227434@qq.com)