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    Large Scale Architectural Asset Extraction from Panoramic Imagery

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    09145640.pdf
    Size:
    27.31Mb
    Format:
    PDF
    Description:
    Accepted Manuscript
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    Type
    Article
    Authors
    Zhu, Peihao cc
    Para, Wamiq Reyaz
    Fruehstueck, Anna cc
    Femiani, John
    Wonka, Peter cc
    KAUST Department
    Computer Science
    Computer Science Program
    Computer, Electrical and Mathematical Science and Engineering (CEMSE) Division
    Visual Computing Center (VCC)
    Date
    2020
    Permanent link to this record
    http://hdl.handle.net/10754/668200
    
    Metadata
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    Abstract
    We present a system to extract architectural assets from large-scale collections of panoramic imagery. We automatically rectify and crop parts of the panoramic image that contain dominant planes, and then use object detection to extract assets such as facades and windows. We also provide various tools to identify attributes of the assets to determine the asset quality and index the assets for search. In addition, we propose a UI to visualize and query assets. Finally, we present applications for urban modeling and texture synthesis.
    Citation
    Zhu, P., Para, W. R., Fruehstueck, A., Femiani, J., & Wonka, P. (2020). Large Scale Architectural Asset Extraction from Panoramic Imagery. IEEE Transactions on Visualization and Computer Graphics, 1–1. doi:10.1109/tvcg.2020.3010694
    Publisher
    Institute of Electrical and Electronics Engineers (IEEE)
    Journal
    IEEE Transactions on Visualization and Computer Graphics
    DOI
    10.1109/TVCG.2020.3010694
    Additional Links
    https://ieeexplore.ieee.org/document/9145640/
    https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9145640
    ae974a485f413a2113503eed53cd6c53
    10.1109/TVCG.2020.3010694
    Scopus Count
    Collections
    Articles; Computer Science Program; Visual Computing Center (VCC); Computer, Electrical and Mathematical Science and Engineering (CEMSE) Division

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