Laser & Optoelectronics Progress, Volume. 62, Issue 2, 0215007(2025)
A Novel Three-Dimensional Point Cloud Matching Algorithm Based on Point Region Features and Weighted Voting
Fig. 3. Features of different planes. (a) Point domain features on a plane; (b) intra-region normal vector on a plane; (c) point domain features on a surface; (d) intra-region normal vector on a surface
Fig. 7. Test subject point cloud. (a) Wrench; (b) steel pipe; (c) T-shaped PVC pipe
Fig. 8. Influence of λ value on matching results. (a) Effect of λ on the number of clustering results of coarsely matched poses of different parts; (b) effect of λ on the RMSE of the estimation of coarse matching poses of different parts; (c) effect of λ on the MAE of the estimation of coarse matching poses of different parts
Fig. 11. Mismatches problems in the test. (a) Reverse matching; (b) translational matching
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Junjun Lu, Ke Ding, Zuoxi Zhao, Feng Wang. A Novel Three-Dimensional Point Cloud Matching Algorithm Based on Point Region Features and Weighted Voting[J]. Laser & Optoelectronics Progress, 2025, 62(2): 0215007
Category: Machine Vision
Received: Apr. 8, 2024
Accepted: Jun. 12, 2024
Published Online: Jan. 6, 2025
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CSTR:32186.14.LOP241055