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    Visual Analytics for Multitemporal Aerial Image Georeferencing

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    Date
    2017
    Author
    Amor-Amorós, Albert
    Federico, Paolo
    Miksch, Silvia ORCID
    Zambanini, Sebastian
    Brenner, Simon
    Sablatnig, Robert
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    Abstract
    Georeferencing of multitemporal aerial imagery is a time-consuming and challenging task that typically requires a high degree of human intervention, and which appears in application domains of critical importance, like unexploded ordnance detection. In order to make a semi-automatic scenario possible, we introduce a Visual Analytics approach for multitemporal aerial image georeferencing designed in close collaboration with real-world analysts that face the problem on a daily basis, and implemented by combining computer vision and interactive visual exploration methods. We report on informal validation findings resulting from the integration of our solution into our users' GIS platform of choice, which positively illustrate its effectiveness and time-saving potential.
    BibTeX
    @inproceedings {10.2312:eurova.20171120,
    booktitle = {EuroVis Workshop on Visual Analytics (EuroVA)},
    editor = {Michael Sedlmair and Christian Tominski},
    title = {{Visual Analytics for Multitemporal Aerial Image Georeferencing}},
    author = {Amor-Amorós, Albert and Federico, Paolo and Miksch, Silvia and Zambanini, Sebastian and Brenner, Simon and Sablatnig, Robert},
    year = {2017},
    publisher = {The Eurographics Association},
    ISBN = {978-3-03868-042-0},
    DOI = {10.2312/eurova.20171120}
    }
    URI
    http://dx.doi.org/10.2312/eurova.20171120
    https://diglib.eg.org:443/handle/10.2312/eurova20171120
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    Eurographics Association copyright © 2013 - 2023 
    Send Feedback | Contact - Imprint | Data Privacy Policy | Disable Google Analytics
    Theme by @mire NV
    System hosted at  Graz University of Technology.
    TUGFhA