Tentative Tests on Two Rapid Multispectral Classifiers for Classifying Point Clouds

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    Abstract

    This paper focusses on the feasibility of classifiers, developed for classifying multispectral images, for assigning classes to point clouds of urban scenes. The motivation of our research is that dense point clouds require fast classification methods to extract meaningful information within a reasonable amount of time and multispectral classifiers do have this property. We employ two encoding methods acting on one feature: the altitude above street level. We emphasize computation time and therefore we use just one feature in this prelimina
    Original languageEnglish
    Title of host publicationProceedings of the 20th AGILE Conference on Geographic Information Science
    Subtitle of host publicationSocietal Geo-innovation
    EditorsArnold Bregt, Tapani Sarjakoski, Ron van Lammeren, Frans Rip
    PublisherWageningen University
    Number of pages2
    ISBN (Electronic)978-90-816960-7-4
    Publication statusPublished - 2017
    EventAGILE 2017: 20th AGILE International Conference on Geographic Information Science - Wageningen, Netherlands
    Duration: 9 May 201712 May 2017
    https://agile-online.org/index.php/conference/conference-2017

    Conference

    ConferenceAGILE 2017: 20th AGILE International Conference on Geographic Information Science
    CountryNetherlands
    CityWageningen
    Period9/05/1712/05/17
    Internet address

    Keywords

    • Classification
    • point clouds
    • feature encoding

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