Semantic classification of 3D point clouds with multiscale spherical neighborhoods

H Thomas, F Goulette, JE Deschaud… - … conference on 3D …, 2018 - ieeexplore.ieee.org
This paper introduces a new definition of multiscale neighborhoods in 3D point clouds. This
definition, based on spherical neighborhoods and proportional subsampling, allows the …

A structured regularization framework for spatially smoothing semantic labelings of 3D point clouds

L Landrieu, H Raguet, B Vallet, C Mallet… - ISPRS Journal of …, 2017 - Elsevier
In this paper, we introduce a mathematical framework for obtaining spatially smooth
semantic labelings of 3D point clouds from a pointwise classification. We argue that …

Classification of large-scale mobile laser scanning data in urban area with LightGBM

E Sevgen, S Abdikan - Remote Sensing, 2023 - mdpi.com
Automatic point cloud classification (PCC) is a challenging task in large-scale urban point
clouds due to the heterogeneous density of points, the high number of points and the …

A classification-segmentation framework for the detection of individual trees in dense MMS point cloud data acquired in urban areas

M Weinmann, M Weinmann, C Mallet, M Brédif - Remote Sensing, 2017 - mdpi.com
In this paper, we present a novel framework for detecting individual trees in densely
sampled 3D point cloud data acquired in urban areas. Given a 3D point cloud, the objective …

Supervised classification of power lines from airborne LiDAR data in urban areas

Y Wang, Q Chen, L Liu, D Zheng, C Li, K Li - Remote Sensing, 2017 - mdpi.com
Automatic extraction of power lines using airborne LiDAR (Light Detection and Ranging)
data has been one of the most important topics for electric power management. However …

A machine learning approach for the detection of supporting rock bolts from laser scan data in an underground mine

J Gallwey, M Eyre, J Coggan - Tunnelling and Underground Space …, 2021 - Elsevier
Rock bolts are a crucial part of underground infrastructure support; however, current
methods to locate and record their positions are manual, time consuming and generally …

Modelling of buildings from aerial LiDAR point clouds using TINs and label maps

M Li, F Rottensteiner, C Heipke - ISPRS Journal of Photogrammetry and …, 2019 - Elsevier
This paper presents a new framework for automatically creating compact building models
from aerial LiDAR point clouds, where each point is known to belong to the class building …

Hierarchical SVM for Semantic Segmentation of 3D Point Clouds for Infrastructure Scenes

M Mansour, J Martens, J Blankenbach - Infrastructures, 2024 - mdpi.com
The incorporation of building information modeling (BIM) has brought about significant
advancements in civil engineering, enhancing efficiency and sustainability across project life …

Evaluation of LiDAR-derived features relevance and training data minimization for 3D point cloud classification

S Morsy, A Shaker - Remote Sensing, 2022 - mdpi.com
Terrestrial laser scanning (TLS) is a leading technology in data acquisition for building
information modeling (BIM) applications due to its rapid, direct, and accurate scanning of …

Automatic pylon extraction using color-aided classification from UAV LiDAR point cloud data

J Huang, Y Shen, J Wang… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Extracting pylons from point clouds gathered by unmanned aerial vehicle LiDAR systems
(UAVLS) is challenging, particularly in complex environments. The difficulty arises due to the …