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

87 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. Semantic Segmentation of 3D LiDAR Data in Dynamic Scene Using Semi-Supervised Learning J. Mei et al. 10.1109/TITS.2019.2919741
6. Comparison of Different Feature Sets for TLS Point Cloud Classification Q. Li & X. Cheng 10.3390/s18124206
7. 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
8. 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
9. Non-Temporal Point Cloud Analysis for Surface Damage in Civil Structures M. Mohammadi et al. 10.3390/ijgi8120527
10. 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
11. Learning multiscale spatial context for three-dimensional point cloud semantic segmentation Y. Wang & S. Xiao 10.1117/1.JEI.29.6.063005
12. 3D Point Cloud Analysis and Classification in Large-Scale Scene Based on Deep Learning L. Wang et al. 10.1109/ACCESS.2019.2909742
13. Active and incremental learning for semantic ALS point cloud segmentation Y. Lin et al. 10.1016/j.isprsjprs.2020.09.003
14. Supervoxel-based extraction and classification of pole-like objects from MLS point cloud data J. Li & X. Cheng 10.1016/j.optlastec.2021.107562
15. 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
16. Outdoor Scene Understanding Based on Multi-Scale PBA Image Features and Point Cloud Features Y. Liu et al. 10.3390/s19204546
17. 3D multi-robot patrolling with a two-level coordination strategy L. Freda et al. 10.1007/s10514-018-09822-3
18. 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
19. Building Extraction from Airborne LiDAR Data Based on Min-Cut and Improved Post-Processing K. Liu et al. 10.3390/rs12172849
20. A Maximum Entropy-Based Optimal Neighbor Selection for Multispectral Airborne LiDAR Point Cloud Classification G. Jiang et al. 10.1109/TGRS.2023.3323963
21. A Machine Learning-Enhanced Digital Twin Approach for Human-Robot-Collaboration K. Dröder et al. 10.1016/j.procir.2018.02.010
22. 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
23. 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
24. Power Line Extraction and Reconstruction Methods from Laser Scanning Data: A Literature Review N. Munir et al. 10.3390/rs15040973
25. 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
26. RLS-LCD: An Efficient Loop Closure Detection for Rotary-LiDAR Scans Q. Zhang et al. 10.1109/JSEN.2023.3345649
27. An Improved RANSAC for 3D Point Cloud Plane Segmentation Based on Normal Distribution Transformation Cells L. Li et al. 10.3390/rs9050433
28. Effective Selection of Variable Point Neighbourhood for Feature Point Extraction from Aerial Building Point Cloud Data E. Dey et al. 10.3390/rs13081520
29. An Inverse Node Graph-Based Method for the Urban Scene Segmentation of 3D Point Clouds B. Zhao et al. 10.3390/rs13153021
30. 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
31. Geometric Feedback System for Robotic Spraying V. Frangez et al. 10.1007/s41064-022-00219-7
32. Towards a Meaningful 3D Map Using a 3D Lidar and a Camera J. Jeong et al. 10.3390/s18082571
33. Multi-Scale Local Context Embedding for LiDAR Point Cloud Classification R. Huang et al. 10.1109/LGRS.2019.2927779
34. 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
35. 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
36. Deep Learning-based Highlighting Visualization for Soft Edges in Large-Scale Scanned Point Clouds W. Li et al. 10.15748/jasse.9.278
37. Optimized LOAM Using Ground Plane Constraints and SegMatch-Based Loop Detection X. Liu et al. 10.3390/s19245419
38. 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
39. Encoding 3D Point Contexts for Self-Supervised Spall Classification Using 3D Bridge Point Clouds V. Kasireddy & B. Akinci 10.1061/JCCEE5.CPENG-5041
40. Automated Feature-Based Down-Sampling Approaches for Fine Registration of Irregular Point Clouds A. Al-Rawabdeh et al. 10.3390/rs12071224
41. Adaptive Framework for the Delineation of Homogeneous Forest Areas Based on LiDAR Points M. Bruggisser et al. 10.3390/rs11020189
42. 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
43. Robust Segmentation for Large Volumes of Laser Scanning Three-Dimensional Point Cloud Data A. Nurunnabi et al. 10.1109/TGRS.2016.2551546
44. Feature selection for airborne LiDAR data filtering: a mutual information method with Parzon window optimization Z. Cai et al. 10.1080/15481603.2019.1695406
45. 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
46. 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
47. Path Segmentation from Point Cloud Data for Autonomous Navigation K. Rajathi et al. 10.3390/app13063977
48. Revue des descripteurs tridimensionnels (3D) pour la catégorisation des nuages de points acquis avec un système LiDAR de télémétrie mobile S. Daniel 10.1139/geomat-2018-0001
49. LPD-AE: Latent Space Representation of Large-Scale 3D Point Cloud C. Suo et al. 10.1109/ACCESS.2020.2999727
50. Lithic or metal tools: Techno-traceological and 3D analysis of rock art L. Zotkina & V. Kovalev 10.1016/j.daach.2019.e00099
51. RING++: Roto-Translation Invariant Gram for Global Localization on a Sparse Scan Map X. Xu et al. 10.1109/TRO.2023.3303035
52. SegMap: Segment-based mapping and localization using data-driven descriptors R. Dubé et al. 10.1177/0278364919863090
53. Correspondence-driven plane-based M3C2 for lower uncertainty in 3D topographic change quantification V. Zahs et al. 10.1016/j.isprsjprs.2021.11.018
54. 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
55. Segmentation-based classification for 3D point clouds in the road environment B. Xiang et al. 10.1080/01431161.2018.1455235
56. Quantifying Multi-Scale Performance of Geometric Features for Efficient Extraction of Insulators from Point Clouds J. Tang et al. 10.3390/rs15133339
57. Leaf Movements of Indoor Plants Monitored by Terrestrial LiDAR M. Herrero-Huerta et al. 10.3389/fpls.2018.00189
58. Refinement of Individual Tree Detection Results Obtained from Airborne Laser Scanning Data for a Mixed Natural Forest N. Brodić et al. 10.3390/rs14215345
59. Urban 3D modeling using mobile laser scanning: a review C. Wang et al. 10.1016/j.vrih.2020.05.003
60. Automatic point cloud coarse registration using geometric keypoint descriptors for indoor scenes M. Bueno et al. 10.1016/j.autcon.2017.06.016
61. 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
62. 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
63. 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
64. Conditional Random Field Features and Structure Assessment for Digital Terrain Modeling T. Arevalo-Ramirez & F. Auat Cheein 10.1109/ACCESS.2021.3061371
65. Context-Aware Network for Semantic Segmentation Toward Large-Scale Point Clouds in Urban Environments C. Liu et al. 10.1109/TGRS.2022.3182776
66. Computational Methods of Acquisition and Processing of 3D Point Cloud Data for Construction Applications Q. Wang et al. 10.1007/s11831-019-09320-4
67. 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
68. Incorporating Human Domain Knowledge in 3-D LiDAR-Based Semantic Segmentation J. Mei & H. Zhao 10.1109/TIV.2019.2955851
69. Land Cover Classification with Multispectral LiDAR Based on Multi-Scale Spatial and Spectral Feature Selection S. Shi et al. 10.3390/rs13204118
70. Incremental-Segment-Based Localization in 3-D Point Clouds R. Dube et al. 10.1109/LRA.2018.2803213
71. Semantic Segmentation for Digital Archives of Borobudur Reliefs Based on Soft-Edge Enhanced Deep Learning S. Ji et al. 10.3390/rs15040956
72. 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
73. A spatial–spectral classification framework for multispectral LiDAR S. Shi et al. 10.1080/10095020.2023.2208611
74. Semantic point cloud interpretation based on optimal neighborhoods, relevant features and efficient classifiers M. Weinmann et al. 10.1016/j.isprsjprs.2015.01.016
75. Quality-based registration refinement of airborne LiDAR and photogrammetric point clouds I. Toschi et al. 10.1016/j.isprsjprs.2020.12.005
76. A Method for Detecting Dynamic Objects Using 2D LiDAR Based on Scan Matching M. Mihálik et al. 10.3390/app12115641
77. 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
78. Classification of ALS Point Cloud with Improved Point Cloud Segmentation and Random Forests H. Ni et al. 10.3390/rs9030288
79. 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
80. 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
81. 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
82. 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
83. A Large-Scale Evaluation Of Shape-Aware Neighborhood Weights And Neighborhood Sizes M. Skrodzki & E. Zimmermann 10.1016/j.cad.2021.103107
84. Utilizing UAV and 3D Computer Vision for Visual Inspection of a Large Gravity Dam A. Khaloo et al. 10.3389/fbuil.2018.00031
85. Evaluation of data subsampling and neighbourhood selection for mobile LiDAR data classification M. Mohamed et al. 10.1016/j.ejrs.2021.04.003
86. Separating Tree Photosynthetic and Non-Photosynthetic Components from Point Cloud Data Using Dynamic Segment Merging D. Wang et al. 10.3390/f9050252
87. A Novel Pallet Detection Method for Automated Guided Vehicles Based on Point Cloud Data Y. Shao et al. 10.3390/s22208019