Curb detection and accessibility evaluation from low-density mobile mapping point cloud data

Kiichiro Ishikawa, Daisuke Kubo, Yoshiharu Amano

    研究成果: Article

    1 引用 (Scopus)

    抜粋

    Our goal is to automatically classify objects from Mobile Mapping System data to enable the automatic construction of dynamic maps. We aimed at the extraction of curbstones and classification of curb types. Although there is much research about curbstones being recognized from laser-scanned point clouds, there are few methods to classify curb types. In this paper, we propose a method to extract curbstones from low-density-type laser scan data. We also propose a method to distinguish whether curbstones allow access to off-road facilities. Evaluation tests give an F-measure of ≥94.4% and an accessibility classification accuracy of ≥99.6%. Moreover, the results of applying multiple filters to noise removal are compared.

    元の言語English
    ページ(範囲)376-385
    ページ数10
    ジャーナルInternational Journal of Automation Technology
    12
    発行部数3
    DOI
    出版物ステータスPublished - 2018 5 1

    ASJC Scopus subject areas

    • Mechanical Engineering
    • Industrial and Manufacturing Engineering

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