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
[14] Chang Y H, Chen N S, Rao L et al. Lidar point cloud descriptor with rotation and translation invariance in dynamic environment[J]. Acta Optica Sinica, 42, 2401007(2022).
[22] Zhou L, Zhao B, Liang D et al. LDASH: a local feature descriptor of point cloud with high discrimination and strong robustness[J]. Laser & Optoelectronics Progress, 61, 1215007(2024).
[26] Yu H S, Fu Q, Sun J et al. Improved 3D-NDT point cloud registration algorithm for indoor mobile robot[J]. Chinese Journal of Scientific Instrument, 40, 151-161(2019).
Get Citation
Copy Citation Text
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
The Author Email:
CSTR:32186.14.LOP241055