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    Plane Segmentation and Registration of Sparse and Heterogeneous Mobile Laser Scanning Point Clouds

    Nguyen H L 2018.pdf (4.966Mb)
    Access Status
    Open access
    Authors
    Nguyen, Hoang Long
    Date
    2018
    Supervisor
    David Belton
    Type
    Thesis
    Award
    PhD
    
    Metadata
    Show full item record
    Faculty
    Science and Engineering
    School
    School of Earth and Planetary Sciences
    URI
    http://hdl.handle.net/20.500.11937/75305
    Collection
    • Curtin Theses
    Abstract

    This research discussed and analysed the limitations of different state of the art methods for point cloud processing tasks due to the sparseness and the heterogeneousness of the MLS point clouds. A novel plane detection and segmentation method for sparse MLS point clouds is proposed. Finally, the most suitable techniques for automatic registration of MLS sparse point clouds were determined based on a new error metric for evaluation.

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