Classification of mobile laser scanning point clouds of urban scenes exploiting cylindrical neighbourhoods

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    This paper presents our work on automated classification of Mobile Laser Scanning (MLS) point clouds of urban scenes with features derived from cylinders around points of consideration. The core of our method consists of spanning up a cylinder around points and deriving features, such as reflectance, height difference, from the points present within the cylindrical neighbourhood. Crucial in the approach is the selection of features from the points within the cylinder. An overall accuracy could be achieved, exploiting two bench mark data sets (Paris-rue-Madame and IQmulus & TerraMobilita) of 83% and 87% respectively.

    Original languageEnglish
    Title of host publicationInternational Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
    Number of pages4
    Publication statusPublished - 2018
    EventISPRS TC II Mid-term Symposium: Towards Photogrammetry 2020 - Riva del Garda, Italy
    Duration: 4 Jun 20187 Jun 2018


    ConferenceISPRS TC II Mid-term Symposium
    CityRiva del Garda


    • 3D Mapping
    • Classification
    • Cylindrical Approach
    • Feature extraction
    • Mobile laser scanning
    • Point clouds

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