Infrared and Laser Engineering, Volume. 51, Issue 12, 20220114(2022)
Robust multi-view registration method for narrow scenes
Fig. 4. Diagram of structured light measuring equipment. (a) High-speed projectors;(b), (c) Industrial camera;(d) Scanning head
Fig. 5. Tooth model data. (a) Complete model and four single-perspective point cloud; (b) Scanning path
Fig. 6. Result comparison of adjacent point cloud registration. (1) ICP; (2) Generalized ICP; (3) FPFH-based method; (4) MRA
Fig. 7. Convergence curves of four algorithms. (a) View 37 and 38; (b) View 210 and 211
Fig. 8. Comparison of overall results of adjacent point cloud registration. (a) ICP; (b) Generalized ICP; (c) FPFH-based method; (d) MRA
Fig. 9. Comparison of overall results of multi-view point cloud registration. (a) Ref.[15] method; (b) Proposed method
Fig. 10. Comparison of loop closure detection results. (a) View 132 and 192; (b) View 96 and 244; (c) View 96 and 252
Fig. 12. Other models and multi-view point cloud registration results. The size of the four objects : (a) 50 mm 70 mm; (b) 53 mm 75 mm; (c) 63 mm 60 mm; (d) 50 mm 50 mm 其他模型及多视角点云配准结果图。四种物体的尺寸:(a) 50 mm 70 mm;(b) 53 mm 75 mm:(c) 63 mm 60 mm;(d) 50 mm 50 mm
|
|
|
|
|
|
Get Citation
Copy Citation Text
Fei Liu, Hanlin Huang, Tian Yang, Wenbo Li, Yang Yang. Robust multi-view registration method for narrow scenes[J]. Infrared and Laser Engineering, 2022, 51(12): 20220114
Category: Photoelectric measurement
Received: Feb. 21, 2022
Accepted: Apr. 1, 2022
Published Online: Jan. 10, 2023
The Author Email: