Folkioneer: Efficient Browsing of Community Geotagged Images on a Worldwide Scale

Abstract : In this paper, we introduce Folkioneer, a novel approach for browsing and exploring community-contributed geotagged images. Initially, images are clustered based on the embedded geographical information by applying an enhanced version of the CURE algorithm, and characteristic geodesic shapes are derived using Delaunay triangulation. Next, images of each geographical cluster are analyzed and grouped according to visual similarity using SURF and restricted homography estimation. At the same time, LDA is used to extract representative topics from the provided tags. Finally, the extracted information is visualized in an intuitive and user-friendly manner with the help of an interactive map.
Document type :
Poster communications
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https://hal.archives-ouvertes.fr/hal-01269808
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Submitted on : Friday, February 5, 2016 - 12:11:05 PM
Last modification on : Friday, January 11, 2019 - 5:09:21 PM

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  • HAL Id : hal-01269808, version 1

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Hatem Mousselly-Sergieh, Daniel Watzinger, Huber Huber, Mario Döller, Elod Egyed-Zsigmond, et al.. Folkioneer: Efficient Browsing of Community Geotagged Images on a Worldwide Scale. International Conference on MultiMedia Modeling - MMM2014, Jan 2014, Dublin, Ireland. pp.361-364, 2014. ⟨hal-01269808⟩

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