Semantic 3D scene interpretation: A framework combining optimal neighborhood size selection with relevant features

103 citations as recorded by crossref.

1. Street environment change detection from mobile laser scanning point clouds W. Xiao et al. 10.1016/j.isprsjprs.2015.04.011
2. Comparative Evaluation of LiDAR systems for transport infrastructure: case studies and performance analysis R. Rashdi et al. 10.1080/22797254.2024.2316304
3. Application of Stochastic Point-Based Rendering to Laser-Scanned Point Clouds of Various Cultural Heritage Objects K. Hasegawa et al. 10.20965/ijat.2018.p0348
4. Distinctive 2D and 3D features for automated large-scale scene analysis in urban areas M. Weinmann et al. 10.1016/j.cag.2015.01.006
5. Point cloud semantic segmentation of grotto scenes using the knowledge-guided deep learning method S. Yang et al. 10.1080/17538947.2024.2385081
6. Semantic Segmentation of 3D LiDAR Data in Dynamic Scene Using Semi-Supervised Learning J. Mei et al. 10.1109/TITS.2019.2919741
7. Comparison of Different Feature Sets for TLS Point Cloud Classification Q. Li & X. Cheng 10.3390/s18124206
8. Edge highlighting of laser-scanned point clouds improves the accuracy of perceived depth in transparent multi-view 3D visualizations D. Aoi et al. 10.1142/S1793962324500211
9. Local and global encoder network for semantic segmentation of Airborne laser scanning point clouds Y. Lin et al. 10.1016/j.isprsjprs.2021.04.016
10. Non-Temporal Point Cloud Analysis for Surface Damage in Civil Structures M. Mohammadi et al. 10.3390/ijgi8120527
11. An Over-Segmentation-Based Uphill Clustering Method for Individual Trees Extraction in Urban Street Areas From MLS Data J. Li et al. 10.1109/JSTARS.2021.3051653
12. Learning multiscale spatial context for three-dimensional point cloud semantic segmentation Y. Wang & S. Xiao 10.1117/1.JEI.29.6.063005
13. 3D Point Cloud Analysis and Classification in Large-Scale Scene Based on Deep Learning L. Wang et al. 10.1109/ACCESS.2019.2909742
14. Active and incremental learning for semantic ALS point cloud segmentation Y. Lin et al. 10.1016/j.isprsjprs.2020.09.003
15. Supervoxel-based extraction and classification of pole-like objects from MLS point cloud data J. Li & X. Cheng 10.1016/j.optlastec.2021.107562
16. Assessing the impact of 3D point neighborhood size selection on unsupervised spall classification with 3D bridge point clouds V. Kasireddy & B. Akinci 10.1016/j.aei.2022.101624
17. Outdoor Scene Understanding Based on Multi-Scale PBA Image Features and Point Cloud Features Y. Liu et al. 10.3390/s19204546
18. Evaluation of LiDAR-Derived Features Relevance and Training Data Minimization for 3D Point Cloud Classification S. Morsy & A. Shaker 10.3390/rs14235934
19. 3D multi-robot patrolling with a two-level coordination strategy L. Freda et al. 10.1007/s10514-018-09822-3
20. A new feature selection from lidar data and digital aerial images acquired for an urban/c environment using an ANFIS-based classification and a fuzzy rough set method P. Pahlavani et al. 10.1080/01431161.2015.1066524
21. Building Extraction from Airborne LiDAR Data Based on Min-Cut and Improved Post-Processing K. Liu et al. 10.3390/rs12172849
22. 3D Lidar Point Cloud Segmentation for Automated Driving R. Abbasi et al. 10.1109/MITS.2023.3325854
23. Geometric characterization and segmentation of historic buildings using classification algorithms and convolutional networks in HBIM J. Moyano et al. 10.1016/j.autcon.2024.105728
24. A Maximum Entropy-Based Optimal Neighbor Selection for Multispectral Airborne LiDAR Point Cloud Classification G. Jiang et al. 10.1109/TGRS.2023.3323963
25. A Machine Learning-Enhanced Digital Twin Approach for Human-Robot-Collaboration K. Dröder et al. 10.1016/j.procir.2018.02.010
26. 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
27. 3-D LiDAR-Based Place Recognition Techniques: A Review of the Past Ten Years Z. Du et al. 10.1109/TIM.2024.3403194
28. Automated semantic segmentation of bridge components from large-scale point clouds using a weighted superpoint graph X. Yang et al. 10.1016/j.autcon.2022.104519
29. Power Line Extraction and Reconstruction Methods from Laser Scanning Data: A Literature Review N. Munir et al. 10.3390/rs15040973
30. Hierarchical SVM for Semantic Segmentation of 3D Point Clouds for Infrastructure Scenes M. Mansour et al. 10.3390/infrastructures9050083
31. Building Extraction from Terrestrial Laser Scanning Data with Density of Projected Points on Polar Grid and Adaptive Threshold M. Chen et al. 10.3390/rs13214392
32. EIDU-Net: edge-preserved inception DenseGCN U-Net for LiDAR point cloud segmentation X. Xu et al. 10.1038/s41598-024-74690-0
33. RLS-LCD: An Efficient Loop Closure Detection for Rotary-LiDAR Scans Q. Zhang et al. 10.1109/JSEN.2023.3345649
34. Effective Selection of Variable Point Neighbourhood for Feature Point Extraction from Aerial Building Point Cloud Data E. Dey et al. 10.3390/rs13081520
35. Separating Leaf and Wood Points in Terrestrial Laser Scanning Data Using Multiple Optimal Scales J. Zhou et al. 10.3390/s19081852
36. Bilevel Thresholding–Based Iterative Analysis for Building-Surface Damage Detection in a Postearthquake Environment M. Areti & Z. Hasnain 10.1061/(ASCE)CP.1943-5487.0001036
37. Geometric Feedback System for Robotic Spraying V. Frangez et al. 10.1007/s41064-022-00219-7
38. Towards a Meaningful 3D Map Using a 3D Lidar and a Camera J. Jeong et al. 10.3390/s18082571
39. Multi-Scale Local Context Embedding for LiDAR Point Cloud Classification R. Huang et al. 10.1109/LGRS.2019.2927779
40. 3D reconstruction of Borobudur reliefs from 2D monocular photographs based on soft-edge enhanced deep learning J. Pan et al. 10.1016/j.isprsjprs.2021.11.007
41. Deep Learning-Based Point Upsampling for Edge Enhancement of 3D-Scanned Data and Its Application to Transparent Visualization W. Li et al. 10.3390/rs13132526
42. Deep Learning-based Highlighting Visualization for Soft Edges in Large-Scale Scanned Point Clouds W. Li et al. 10.15748/jasse.9.278
43. Optimized LOAM Using Ground Plane Constraints and SegMatch-Based Loop Detection X. Liu et al. 10.3390/s19245419
44. An Adaptive End-to-End Classification Approach for Mobile Laser Scanning Point Clouds Based on Knowledge in Urban Scenes M. Zheng et al. 10.3390/rs11020186
45. Encoding 3D Point Contexts for Self-Supervised Spall Classification Using 3D Bridge Point Clouds V. Kasireddy & B. Akinci 10.1061/JCCEE5.CPENG-5041
46. Automated Feature-Based Down-Sampling Approaches for Fine Registration of Irregular Point Clouds A. Al-Rawabdeh et al. 10.3390/rs12071224
47. Adaptive Framework for the Delineation of Homogeneous Forest Areas Based on LiDAR Points M. Bruggisser et al. 10.3390/rs11020189
48. Validation of fracture data recognition in rock masses by automated plane detection in 3D point clouds T. Drews et al. 10.1016/j.ijrmms.2018.06.023
49. Robust Segmentation for Large Volumes of Laser Scanning Three-Dimensional Point Cloud Data A. Nurunnabi et al. 10.1109/TGRS.2016.2551546
50. Feature selection for airborne LiDAR data filtering: a mutual information method with Parzon window optimization Z. Cai et al. 10.1080/15481603.2019.1695406
51. A Novel Octree-Based 3-D Fully Convolutional Neural Network for Point Cloud Classification in Road Environment B. Xiang et al. 10.1109/TGRS.2019.2916625
52. 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
53. Path Segmentation from Point Cloud Data for Autonomous Navigation K. Rajathi et al. 10.3390/app13063977
54. LPD-AE: Latent Space Representation of Large-Scale 3D Point Cloud C. Suo et al. 10.1109/ACCESS.2020.2999727
55. Integrated Change Detection and Classification in Urban Areas Based on Airborne Laser Scanning Point Clouds T. Tran et al. 10.3390/s18020448
56. Lithic or metal tools: Techno-traceological and 3D analysis of rock art L. Zotkina & V. Kovalev 10.1016/j.daach.2019.e00099
57. Segmentation of Façades from Urban 3D Point Clouds Using Geometrical and Morphological Attribute-Based Operators A. Serna et al. 10.3390/ijgi5010006
58. RING++: Roto-Translation Invariant Gram for Global Localization on a Sparse Scan Map X. Xu et al. 10.1109/TRO.2023.3303035
59. SegMap: Segment-based mapping and localization using data-driven descriptors R. Dubé et al. 10.1177/0278364919863090
60. Correspondence-driven plane-based M3C2 for lower uncertainty in 3D topographic change quantification V. Zahs et al. 10.1016/j.isprsjprs.2021.11.018
61. Comparison of low-altitude UAV photogrammetry with terrestrial laser scanning as data-source methods for terrain covered in low vegetation W. Gruszczyński et al. 10.1016/j.isprsjprs.2017.02.015
62. Segmentation-based classification for 3D point clouds in the road environment B. Xiang et al. 10.1080/01431161.2018.1455235
63. Machine Learning Vegetation Filtering of Coastal Cliff and Bluff Point Clouds P. Wernette 10.3390/rs16122169
64. Quantifying Multi-Scale Performance of Geometric Features for Efficient Extraction of Insulators from Point Clouds J. Tang et al. 10.3390/rs15133339
65. High-Visibility Edge-Highlighting Visualization of 3D Scanned Point Clouds Based on Dual 3D Edge Extraction Y. Yamada et al. 10.3390/rs16193750
66. Leaf Movements of Indoor Plants Monitored by Terrestrial LiDAR M. Herrero-Huerta et al. 10.3389/fpls.2018.00189
67. Refinement of Individual Tree Detection Results Obtained from Airborne Laser Scanning Data for a Mixed Natural Forest N. Brodić et al. 10.3390/rs14215345
68. Urban 3D modeling using mobile laser scanning: a review C. Wang et al. 10.1016/j.vrih.2020.05.003
69. Automatic point cloud coarse registration using geometric keypoint descriptors for indoor scenes M. Bueno et al. 10.1016/j.autcon.2017.06.016
70. Toward Building and Civil Infrastructure Reconstruction From Point Clouds: A Review on Data and Key Techniques Y. Xu & U. Stilla 10.1109/JSTARS.2021.3060568
71. A novel approach to de-noising 3D point clouds using mean-shift based clustering algorithm s. kamalou et al. 10.52547/jgit.9.4.1
72. Aerial Point Cloud Classification Using an Alternative Approach for the Dynamic Computation of K-Nearest Neighbors I. Pârvu et al. 10.2478/jaes-2020-0023
73. Conditional Random Field Features and Structure Assessment for Digital Terrain Modeling T. Arevalo-Ramirez & F. Auat Cheein 10.1109/ACCESS.2021.3061371
74. Context-Aware Network for Semantic Segmentation Toward Large-Scale Point Clouds in Urban Environments C. Liu et al. 10.1109/TGRS.2022.3182776
75. G3Reg: Pyramid Graph-Based Global Registration Using Gaussian Ellipsoid Model Z. Qiao et al. 10.1109/TASE.2024.3394519
76. Computational Methods of Acquisition and Processing of 3D Point Cloud Data for Construction Applications Q. Wang et al. 10.1007/s11831-019-09320-4
77. 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
78. Segmentation of LiDAR point cloud data in urban areas using adaptive neighborhood selection technique D. Chakraborty et al. 10.1371/journal.pone.0307138
79. Incorporating Human Domain Knowledge in 3-D LiDAR-Based Semantic Segmentation J. Mei & H. Zhao 10.1109/TIV.2019.2955851
80. Land Cover Classification with Multispectral LiDAR Based on Multi-Scale Spatial and Spectral Feature Selection S. Shi et al. 10.3390/rs13204118
81. Data enrichment for semantic segmentation of point clouds for the generation of geometric-semantic road models D. Crampen & J. Blankenbach 10.3389/fbuil.2025.1607375
82. Incremental-Segment-Based Localization in 3-D Point Clouds R. Dube et al. 10.1109/LRA.2018.2803213
83. Semantic Segmentation for Digital Archives of Borobudur Reliefs Based on Soft-Edge Enhanced Deep Learning S. Ji et al. 10.3390/rs15040956
84. BICANet: LiDAR Point Cloud Classification Network Based on Coordinate Attention and Blueprint Separation Involution Neural Network G. Zhang et al. 10.1109/JSEN.2023.3323047
85. Genetic Algorithm Empowering Unsupervised Learning for Optimizing Building Segmentation from Light Detection and Ranging Point Clouds M. Sulaiman et al. 10.3390/rs16193603
86. A spatial–spectral classification framework for multispectral LiDAR S. Shi et al. 10.1080/10095020.2023.2208611
87. Semantic point cloud interpretation based on optimal neighborhoods, relevant features and efficient classifiers M. Weinmann et al. 10.1016/j.isprsjprs.2015.01.016
88. Quality-based registration refinement of airborne LiDAR and photogrammetric point clouds I. Toschi et al. 10.1016/j.isprsjprs.2020.12.005
89. A Method for Detecting Dynamic Objects Using 2D LiDAR Based on Scan Matching M. Mihálik et al. 10.3390/app12115641
90. 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
91. Classification of ALS Point Cloud with Improved Point Cloud Segmentation and Random Forests H. Ni et al. 10.3390/rs9030288
92. PatchAugNet: Patch feature augmentation-based heterogeneous point cloud place recognition in large-scale street scenes X. Zou et al. 10.1016/j.isprsjprs.2023.11.005
93. Revue des descripteurs tridimensionnels (3D) pour la catégorisation des nuages de points acquis avec un système LiDAR de télémétrie mobile S. Daniel 10.1139/geomatica-2018-0001
94. Point Cloud Data Processing Optimization in Spectral and Spatial Dimensions Based on Multispectral Lidar for Urban Single-Wood Extraction S. Shi et al. 10.3390/ijgi12030090
95. Yield prediction by machine learning from UAS-based multi-sensor data fusion in soybean M. Herrero-Huerta et al. 10.1186/s13007-020-00620-6
96. Edge highlighting with depth-dependent opacity gradation of laser-scanned point clouds improves the accuracy of perceived depth in transparent multi-view 3D visualizations D. Aoi et al. 10.1007/s12650-024-01014-9
97. Terrestrial Laser Scanning for Quantifying Timber Assortments from Standing Trees in a Mixed and Multi-Layered Mediterranean Forest C. Alvites et al. 10.3390/rs13214265
98. Utilizing UAV and 3D Computer Vision for Visual Inspection of a Large Gravity Dam A. Khaloo et al. 10.3389/fbuil.2018.00031
99. Evaluation of data subsampling and neighbourhood selection for mobile LiDAR data classification M. Mohamed et al. 10.1016/j.ejrs.2021.04.003
100. Separating Tree Photosynthetic and Non-Photosynthetic Components from Point Cloud Data Using Dynamic Segment Merging D. Wang et al. 10.3390/f9050252
101. A Novel Pallet Detection Method for Automated Guided Vehicles Based on Point Cloud Data Y. Shao et al. 10.3390/s22208019
102. A Small-Object-Detection Algorithm Based on LiDAR Point-Cloud Clustering for Autonomous Vehicles Z. Duan et al. 10.3390/s24165423
103. Total leaf area estimation based on point cloud reduction and resolution grid construction using mobile multi-layer LiDAR scanning Q. Li & L. Ding 10.1016/j.optlastec.2024.112394