GEOMETRIC FEATURES AND THEIR RELEVANCE FOR 3D POINT CLOUD CLASSIFICATION

41 citations as recorded by crossref.

1. Supervised Detection of Façade Openings in 3D Point Clouds with Thermal Attributes M. Jarząbek-Rychard et al. 10.3390/rs12030543
2. Automatic Segmentation of Individual Grains From a Terrestrial Laser Scanning Point Cloud of a Mountain River Bed A. Walicka & N. Pfeifer 10.1109/JSTARS.2022.3141892
3. Generalized Extraction of Bolts, Mesh, and Rock in Tunnel Point Clouds: A Critical Comparison of Geometric Feature-Based Methods Using Random Forest and Neural Networks L. Weidner & G. Walton 10.3390/rs16234466
4. Machine Learning-Based Monitoring for Planning Climate-Resilient Conservation of Built Heritage L. Fiorini et al. 10.3390/drones8060249
5. Large-Scale ALS Data Semantic Classification Integrating Location-Context-Semantics Cues by Higher-Order CRF W. Han et al. 10.3390/s20061700
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7. A deep-learning model for semantic segmentation of meshes from UAV oblique images R. Tang et al. 10.1080/01431161.2022.2111665
8. Extracting Structural Elements From 3D Point Clouds in Indoor Environments via Machine Learning Techniques K. Aksu & H. Demirel 10.1109/ACCESS.2024.3423425
9. Lightweight and rotation-invariant place recognition network for large-scale raw point clouds Z. Zhang et al. 10.1016/j.isprsjprs.2024.04.030
10. Automatic voxel-based 3D indoor reconstruction and room partitioning from triangle meshes P. Hübner et al. 10.1016/j.isprsjprs.2021.07.002
11. Evaluating state-of-the-art 3D scanning methods for stem-level biodiversity inventories in forests C. Fol et al. 10.1016/j.jag.2023.103396
12. Classification using a three-dimensional sensor in a structured industrial environment I. Mikhailov et al. 10.1117/1.JEI.29.4.041008
13. Classification of Terrestrial Laser Scanner Point Clouds: A Comparison of Methods for Landslide Monitoring from Mathematical Surface Approximation G. Kermarrec et al. 10.3390/rs14205099
14. Building a Mycenaean chamber tomb catalogue from terrestrial laser scan data I. Gutierrez et al. 10.1016/j.daach.2024.e00319
15. NSS-MDL: Natural Scene Statistics-guided multi-task deep learning for no-reference point cloud quality assessment S. Bourbia et al. 10.1016/j.iswa.2025.200570
16. Robot Localization in Tunnels: Combining Discrete Features in a Pose Graph Framework T. Seco et al. 10.3390/s22041390
17. A Maximum Entropy-Based Optimal Neighbor Selection for Multispectral Airborne LiDAR Point Cloud Classification G. Jiang et al. 10.1109/TGRS.2023.3323963
18. Machine Learning and Deep Learning for the Built Heritage Analysis: Laser Scanning and UAV-Based Surveying Applications on a Complex Spatial Grid Structure D. Billi et al. 10.3390/rs15081961
19. An algorithm for measuring landslide deformation in terrestrial lidar point clouds using trees L. Weidner et al. 10.1007/s10346-021-01723-4
20. A hierarchical deep neural network with iterative features for semantic labeling of airborne LiDAR point clouds Y. Yang et al. 10.1016/j.cageo.2021.104932
21. Toward a Data Fusion Index for the Assessment and Enhancement of 3D Multimodal Reconstruction of Built Cultural Heritage A. Pamart et al. 10.3390/rs15092408
22. Improvement of 3D LiDAR point cloud classification of urban road environment based on random forest classifier M. Mohamed et al. 10.1080/10106049.2022.2102218
23. Metrological Analysis with Covariance Features of Micro-Channels Fabricated with a Femtosecond Laser M. Verdi et al. 10.3390/metrology4030024
24. Machine Learning Generalisation across Different 3D Architectural Heritage E. Grilli & F. Remondino 10.3390/ijgi9060379
25. Point cloud features suitable for automatic labeling of MMS point cloud data G. TAKAHASHI & H. MASUDA 10.4287/jsprs.60.266
26. Classification of rock slope cavernous weathering on UAV photogrammetric point clouds: The example of Hegra (UNESCO World Heritage Site, Kingdom of Saudi Arabia) T. Beni et al. 10.1016/j.enggeo.2023.107286
27. Two-Layered Graph-Cuts-Based Classification of LiDAR Data in Urban Areas Y. Yang et al. 10.3390/s19214685
28. Extraction of Corresponding Point Cloud Features Based on Least Squares Deviation Analysis Z. Xing et al. 10.54691/rhdwg968
29. Hybrid 3D Reconstruction of Indoor Scenes Integrating Object Recognition M. Li et al. 10.3390/rs16040638
30. Automating the inventory of the navigable space for pedestrians on historical sites: Towards accurate path planning D. Treccani et al. 10.1016/j.jag.2023.103400
31. Stem Detection from Terrestrial Laser Scanning Data with Features Selected via Stem-Based Evaluation M. Chen et al. 10.3390/f14102035
32. Machine Learning Vegetation Filtering of Coastal Cliff and Bluff Point Clouds P. Wernette 10.3390/rs16122169
33. Robust Building Detection in Urban Environments from Airborne LiDAR Data: A Geometry-Based Approach R. dos Santos & M. Galo 10.1109/JSTARS.2024.3391050
34. Inferring an animal’s environment through biologging: quantifying the environmental influence on animal movement J. Eikelboom et al. 10.1186/s40462-020-00228-4
35. Structural segmentation and classification of mobile laser scanning point clouds with large variations in point density Y. Li et al. 10.1016/j.isprsjprs.2019.05.007
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37. Efficient 3D Mapping and Modelling of Indoor Scenes with the Microsoft HoloLens: A Survey M. Weinmann et al. 10.1007/s41064-021-00163-y
38. A Knowledge-Based Multi-Scale Adaptive Classification Approach for Mobile Laser Scanning Point Clouds in Urban Scenes M. Zheng et al. 10.1109/ACCESS.2023.3335607
39. Automated classification of piping components from 3D LiDAR point clouds using SE-PseudoGrid C. Yin et al. 10.1016/j.autcon.2022.104300
40. Evaluation of Class Distribution and Class Combinations on Semantic Segmentation of 3D Point Clouds With PointNet E. Barnefske & H. Sternberg 10.1109/ACCESS.2022.3233411
41. Methodology for Identifying Optimal Pedestrian Paths in an Urban Environment: A Case Study of a School Environment in A Coruña, Spain D. Fernández-Arango et al. 10.3390/smartcities7030060