Machine learning-based segmentation of aerial LiDAR point cloud data on building roof

Article


Dey, Emon Kumar, Awrangjeb, Mohammad, Tarsha Kurdi, Fayez and Stantic, Bela. 2023. "Machine learning-based segmentation of aerial LiDAR point cloud data on building roof." European Journal of Remote Sensing. 56 (1). https://doi.org/10.1080/22797254.2023.2210745
Article Title

Machine learning-based segmentation of aerial LiDAR point cloud data on building roof

ERA Journal ID210444
Article CategoryArticle
AuthorsDey, Emon Kumar, Awrangjeb, Mohammad, Tarsha Kurdi, Fayez and Stantic, Bela
Journal TitleEuropean Journal of Remote Sensing
Journal Citation56 (1)
Article Number2210745
Number of Pages18
Year2023
PublisherTaylor & Francis
Place of PublicationItaly
ISSN1129-8596
2039-7879
2279-7254
Digital Object Identifier (DOI)https://doi.org/10.1080/22797254.2023.2210745
Web Address (URL)https://www.tandfonline.com/doi/full/10.1080/22797254.2023.2210745
AbstractThree-dimensional (3D) reconstruction of a building can be facilitated by correctly segmenting different feature points (e.g. in the form of boundary, fold edge, and planar points) over the building roof, and then, establishing relationships among the constructed feature lines and planar patches using the segmented points. Present machine learning-based segmentation approaches of Light Detection and Ranging (LiDAR) point cloud data are confined only to different object classes or semantic labelling. In the context of fine-grained feature point classification over the extracted building roof, machine learning approaches have not yet been explored. In this paper, after generating the ground truth data for the extracted building roofs from three different datasets, we apply machine learning methods to segment the roof point cloud based on seven different effective geometric features. The goal is not to semantically enhance the point cloud, but rather to facilitate the application of 3D building reconstruction algorithms, making them easier to use. The calculated F1-scores for each class confirm the competitive performances over the state-of-the-art techniques, which are more than 95% almost in each area of the used datasets. © 2023 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.
Keywordsboundary point extraction; Machine learning; building reconstruction; edge point; feature point extraction; segmentation
ANZSRC Field of Research 20204017. Mechanical engineering
Byline AffiliationsGriffith University
School of Surveying and Built Environment
Permalink -

https://research.usq.edu.au/item/z259y/machine-learning-based-segmentation-of-aerial-lidar-point-cloud-data-on-building-roof

  • 53
    total views
  • 36
    total downloads
  • 1
    views this month
  • 2
    downloads this month

Export as

Related outputs

Assessment of NavVis VLX and BLK2GO SLAM Scanner Accuracy for Outdoor and Indoor Surveying Tasks
Gharineiat, Zahra, Tarsha Kurdi, Fayez, Henny, Krish, Gray, Hamish, Jamieson, Aaron and Reeves, Nicholas. 2024. "Assessment of NavVis VLX and BLK2GO SLAM Scanner Accuracy for Outdoor and Indoor Surveying Tasks." Remote Sensing. 16 (17). https://doi.org/10.3390/rs16173256
Accurate Calculation of Upper Biomass Volume of Single Trees Using Matrixial Representation of LiDAR Data
Tarsha Kurdi, Fayez, Lewandowicz, Elzbieta, Gharineiat, Zahra and Shan, Jie. 2024. "Accurate Calculation of Upper Biomass Volume of Single Trees Using Matrixial Representation of LiDAR Data." Remote Sensing. 16 (12). https://doi.org/10.3390/rs16122220
Modeling the Geometry of Tree Trunks Using LiDAR Data
Tarsha Kurdi, Fayez, Gharineiat, Zahra, Lewandowicz, Elzbieta and Shan, Jie. 2024. "Modeling the Geometry of Tree Trunks Using LiDAR Data." Forests. 15 (2). https://doi.org/10.3390/f15020368
Three-Dimensional Modeling and Visualization of Single Tree LiDAR Point Cloud Using Matrixial Form
Tarsha Kurdi, Fayez, Lewandowicz, Elżbieta, Shan, Jie and Gharineiat, Zahra. 2024. "Three-Dimensional Modeling and Visualization of Single Tree LiDAR Point Cloud Using Matrixial Form." IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 17, pp. 3010-3022. https://doi.org/10.1109/JSTARS.2024.3349549
Efficiency of Terrestrial Laser Scanning in Survey Works: Assessment, Modelling, and Monitoring
Tarsha Kurdi, Fayez, Reed, Paul, Gharineiat, Zahra and Awrangjeb, Mohammad. 2023. "Efficiency of Terrestrial Laser Scanning in Survey Works: Assessment, Modelling, and Monitoring." International Journal of Environmental Sciences and Natural Resources. 32 (2). https://doi.org/10.19080/IJESNR.2023.32.556334
3D LoD2 and LoD3 Modelling of Rotating Surface Building of Ornamental Towers starting from LiDAR Data
Lewandowicz, Elzbieta, Tarsha Kurdi, Fayez and Gharineiat, Zahra. 2023. "3D LoD2 and LoD3 Modelling of Rotating Surface Building of Ornamental Towers starting from LiDAR Data." Oniga, Valeria-Ersilia (ed.) Prime Archives in Remote Sensing. India. Vide Leaf.
Modeling Multi-Rotunda Buildings at LoD3 Level from LiDAR Data
Tarsha Kurdi, Fayez, Lewandowicz, Elzbieta, Gharineiat, Zahra and Shan, Jie. 2023. "Modeling Multi-Rotunda Buildings at LoD3 Level from LiDAR Data." Remote Sensing. 15 (13). https://doi.org/10.3390/rs15133324
Contribution of Geometric Feature Analysis for Deep Learning Classification Algorithms of Urban LiDAR Data
Tarsha Kurdi, Fayez, Amakhchan, Wijdan, Gharineiat, Zahra, Boulaassal, Hakim and Kharki, Omar El. 2023. "Contribution of Geometric Feature Analysis for Deep Learning Classification Algorithms of Urban LiDAR Data." Sensors. 23 (17). https://doi.org/10.3390/s23177360
3D LoD2 and LoD3 Modeling of Buildings with Ornamental Towers and Turrets Based on LiDAR Data
Lewandowicz, Elzbieta, Tarsha Kurdi, Fayez and Gharineiat, Zahra. 2022. "3D LoD2 and LoD3 Modeling of Buildings with Ornamental Towers and Turrets Based on LiDAR Data." Remote Sensing. 14 (19), pp. 1-17. https://doi.org/10.3390/rs14194687
Review of Automatic Processing of Topography and Surface Feature Identification LiDAR Data Using Machine Learning Techniques
Gharineiat, Zahra, Tarsha Kurdi, Fayez and Campbell, Glenn. 2022. "Review of Automatic Processing of Topography and Surface Feature Identification LiDAR Data Using Machine Learning Techniques." Remote Sensing. 14 (19), pp. 1-24. https://doi.org/10.3390/rs14194685
Comparative Approach of Unmanned Aerial Vehicle Restrictions in Controlled Airspaces
McTegg, Stephen, Kurdi, Fayez, Simmons, Shane and Gharineiat, Zahra. 2022. "Comparative Approach of Unmanned Aerial Vehicle Restrictions in Controlled Airspaces." Remote Sensing. 14 (4), pp. 1-30. https://doi.org/10.3390/rs14040822
Timed intervention in COVID-19 and panic buying
Prentice, Catherine, Chen, Jinyan and Stantic, Bela. 2020. "Timed intervention in COVID-19 and panic buying." Journal of Retailing and Consumer Services. 57, pp. 1-11. https://doi.org/10.1016/j.jretconser.2020.102203
Relevant, or irrelevant, external factors in panic buying
Prentice, Catherine, Nguyen, Mai, Nandy, Purnima, Winardi, Michael Aswin, Chen, Ying, Le Monkhouse, Lien, Dominique-Ferreira, Sergio and Stantic, Bela. 2021. "Relevant, or irrelevant, external factors in panic buying." Journal of Retailing and Consumer Services. 61, pp. 1-10. https://doi.org/10.1016/j.jretconser.2021.102587
Automatic Filtering of Lidar Building Point Cloud in Case of Trees Associated to Building Roof
Tarsha Kurdi, Fayez, Gharineiat, Zahra, Campbell, Glenn, Awrangjeb, Mohammad and Dey, Emon Kumar. 2022. "Automatic Filtering of Lidar Building Point Cloud in Case of Trees Associated to Building Roof." Remote Sensing. 14 (2), pp. 1-23. https://doi.org/10.3390/rs14020430
Full series algorithm of automatic building extraction and modelling from LiDAR data
Tarsha Kurdi, Fayez, Gharineiat, Zahra, Campbell, Glenn, Dey, Emon Kumar and Awrangjeb, Mohammad. 2021. "Full series algorithm of automatic building extraction and modelling from LiDAR data." Zhou, Jun, Salvado, Olivier, Sohel, Ferdous, Borges, Paulo and Wang, Shilin (ed.) 2021 International Conference on Digital Image Computing: Techniques and Applications (DICTA 2021). Gold Coast, Australia 29 Nov - 01 Dec 2021 United States.
Random forest machine learning technique for automatic vegetation detection and modelling in LiDAR data
Tarsha Kurdi, Fayez, Amakhchan, Wijdan and Gharineiat, Zahra. 2021. "Random forest machine learning technique for automatic vegetation detection and modelling in LiDAR data." International Journal of Environmental Sciences and Natural Resources. 28 (2). https://doi.org/10.19080/IJESNR.2021.28.556234