H-RANSAC: A HYBRID POINT CLOUD SEGMENTATION COMBINING 2D AND 3D DATA

11 citations as recorded by crossref.

1. Point Cloud-Based Smart Building Acceptance System for Surface Quality Evaluation D. Cai et al. 10.3390/buildings13112893
2. Fast plane extraction method based on the point pair feature Z. Xiao et al. 10.1007/s11042-022-14063-9
3. Automated Reconstruction of Existing Building Interior Scene BIMs Using a Feature-Enhanced Point Transformer and an Octree J. Chen et al. 10.3390/app132413239
4. A new approach for roof segmentation from airborne LiDAR point clouds C. Zhao et al. 10.1080/2150704X.2020.1847348
5. RANSAC-based multi primitive building reconstruction from 3D point clouds Z. Li & J. Shan 10.1016/j.isprsjprs.2021.12.012
6. Linking Points With Labels in 3D: A Review of Point Cloud Semantic Segmentation Y. Xie et al. 10.1109/MGRS.2019.2937630
7. Panicle-3D: Efficient Phenotyping Tool for Precise Semantic Segmentation of Rice Panicle Point Cloud L. Gong et al. 10.34133/2021/9838929
8. Facet-Segmentation of Point Cloud Based on Multiscale Hypervoxel Region Growing X. Chen et al. 10.1007/s12524-025-02179-y
9. Towards Automatic Segmentation and Recognition of Multiple Precast Concrete Elements in Outdoor Laser Scan Data J. Liu et al. 10.3390/rs11111383
10. Integrating as-built BIM model from point cloud data in construction projects R. Zeng et al. 10.1108/ECAM-12-2022-1196
11. A LiDAR SLAM Based on Clustering Features and Constraint Separation S. Wang et al. 10.1109/TIM.2025.3544715