TRAJECTORY-BASED REGISTRATION OF 3D LIDAR POINT CLOUDS ACQUIRED WITH A MOBILE MAPPING SYSTEM

8 citations as recorded by crossref.

1. Automated Enhancement of Multimodal Geospatial Data Alignment Through System Calibration and Trajectory Refinement J. Liu & A. Habib https://doi.org/10.1109/JSTARS.2025.3643441
2. Improving the Accuracy of Subway Mobile Laser Scanning Point Clouds Based on Target Constraints H. Liu et al. https://doi.org/10.1061/JSUED2.SUENG-1625
3. SLAM integrated mobile mapping system in complex urban environments S. Li et al. https://doi.org/10.1016/j.isprsjprs.2020.05.012
4. IMU-Aided Registration of MLS Point Clouds Using Inertial Trajectory Error Model and Least Squares Optimization Z. Chen et al. https://doi.org/10.3390/rs14061365
5. Enhance Pose Accuracy of GNSS/INS Integration by Fusing LiDAR Structure Features Based on Continuous-Time State Representation J. Cheng et al. https://doi.org/10.1109/LRA.2025.3597859
6. Position Consistency Correction of Revisit Mobile Laser Scanning Point Cloud in Urban Scene 响. 邹 https://doi.org/10.12677/GST.2019.72015
7. MuCoGraph: A multi-scale constraint enhanced pose-graph framework for MLS point cloud inconsistency correction Y. Li et al. https://doi.org/10.1016/j.isprsjprs.2023.09.018
8. Application of Mobile Mapping System for a Modern Topography M. Arseni et al. https://doi.org/10.2478/jaes-2024-0023