Building and road detection from large aerial imagery

Shunta Saito, Yoshimitsu Aoki

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    32 Citations (Scopus)

    Abstract

    Building and road detection from aerial imagery has many applications in a wide range of areas including urban design, real-estate management, and disaster relief. The extracting buildings and roads from aerial imagery has been performed by human experts manually, so that it has been very costly and time-consuming process. Our goal is to develop a system for automatically detecting buildings and roads directly from aerial imagery. Many attempts at automatic aerial imagery interpretation have been proposed in remote sensing literature, but much of early works use local features to classify each pixel or segment to an object label, so that these kind of approach needs some prior knowledge on object appearance or class-conditional distribution of pixel values. Furthermore, some works also need a segmentation step as pre-processing. Therefore, we use Convolutional Neural Networks(CNN) to learn mapping from raw pixel values in aerial imagery to three object labels (buildings, roads, and others), in other words, we generate three-channel maps from raw aerial imagery input. We take a patch-based semantic segmentation approach, so we firstly divide large aerial imagery into small patches and then train the CNN with those patches and corresponding three-channel map patches. Finally, we evaluate our system on a large-scale road and building detection datasets that is publicly available.

    Original languageEnglish
    Title of host publicationProceedings of SPIE-IS and T Electronic Imaging - Image Processing
    Subtitle of host publicationMachine Vision Applications VIII
    EditorsKurt S. Niel, Edmund Y. Lam
    PublisherSPIE
    ISBN (Electronic)9781628414950
    DOIs
    Publication statusPublished - 2015 Jan 1
    EventImage Processing: Machine Vision Applications VIII - San Francisco, United States
    Duration: 2015 Feb 102015 Feb 11

    Publication series

    NameProceedings of SPIE - The International Society for Optical Engineering
    Volume9405
    ISSN (Print)0277-786X
    ISSN (Electronic)1996-756X

    Other

    OtherImage Processing: Machine Vision Applications VIII
    CountryUnited States
    CitySan Francisco
    Period15/2/1015/2/11

    Keywords

    • Aerial imagery
    • Building detection
    • Convolutional neural networks
    • Road detection
    • Semantic segmentation

    ASJC Scopus subject areas

    • Electronic, Optical and Magnetic Materials
    • Condensed Matter Physics
    • Computer Science Applications
    • Applied Mathematics
    • Electrical and Electronic Engineering

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  • Cite this

    Saito, S., & Aoki, Y. (2015). Building and road detection from large aerial imagery. In K. S. Niel, & E. Y. Lam (Eds.), Proceedings of SPIE-IS and T Electronic Imaging - Image Processing: Machine Vision Applications VIII [94050K] (Proceedings of SPIE - The International Society for Optical Engineering; Vol. 9405). SPIE. https://doi.org/10.1117/12.2083273