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BlueFinder: estimate where a beach photo was taken

Published: 16 April 2012 Publication History

Abstract

This paper describes a system to estimate geographical locations for beach photos. We develop an iterative method that not only trains visual classifiers but also discovers geographical clusters for beach regions. The results show that it is possible to recognize different beaches using visual information with reasonable accuracy, and our system works 27 times better than random guess for the geographical localization task.

References

[1]
L. Cao, J. Yu, J. Luo, and T. Huang. Enhancing semantic and geographic annotation of web images via logistic canonical correlation regression. In ACM Multimedia, 2009.
[2]
D. J. Crandall, L. Backstrom, D. P. Huttenlocher, and J. M. Kleinberg. Mapping the world's photos. WWW, 2009.
[3]
J. Hays and A. A. Efros. IM2PGS: estimating geographic information from a single image. In CVPR, 2008.

Cited By

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  • (2024)PIGEON: Predicting Image Geolocations2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)10.1109/CVPR52733.2024.01225(12893-12902)Online publication date: 16-Jun-2024
  • (2024)Crowdsourced mapping of tourism distribution and dynamics in Iceland using FlickrScandinavian Journal of Hospitality and Tourism10.1080/15022250.2024.2355905(1-17)Online publication date: 23-May-2024
  • (2022)Where in the World Is This Image? Transformer-Based Geo-localization in the WildComputer Vision – ECCV 202210.1007/978-3-031-19839-7_12(196-215)Online publication date: 23-Oct-2022
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  1. BlueFinder: estimate where a beach photo was taken

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    Published In

    cover image ACM Other conferences
    WWW '12 Companion: Proceedings of the 21st International Conference on World Wide Web
    April 2012
    1250 pages
    ISBN:9781450312301
    DOI:10.1145/2187980

    Sponsors

    • Univ. de Lyon: Universite de Lyon

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    Association for Computing Machinery

    New York, NY, United States

    Publication History

    Published: 16 April 2012

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    Author Tags

    1. beach photos
    2. geographical clustering
    3. geographical estimation

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    • Poster

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    WWW 2012
    Sponsor:
    • Univ. de Lyon
    WWW 2012: 21st World Wide Web Conference 2012
    April 16 - 20, 2012
    Lyon, France

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    Overall Acceptance Rate 1,899 of 8,196 submissions, 23%

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    View all
    • (2024)PIGEON: Predicting Image Geolocations2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)10.1109/CVPR52733.2024.01225(12893-12902)Online publication date: 16-Jun-2024
    • (2024)Crowdsourced mapping of tourism distribution and dynamics in Iceland using FlickrScandinavian Journal of Hospitality and Tourism10.1080/15022250.2024.2355905(1-17)Online publication date: 23-May-2024
    • (2022)Where in the World Is This Image? Transformer-Based Geo-localization in the WildComputer Vision – ECCV 202210.1007/978-3-031-19839-7_12(196-215)Online publication date: 23-Oct-2022
    • (2018)Geolocation Estimation of Photos Using a Hierarchical Model and Scene ClassificationComputer Vision – ECCV 201810.1007/978-3-030-01258-8_35(575-592)Online publication date: 6-Oct-2018
    • (2016)Where the Photos Were Taken: Location Prediction by Learning from Flickr PhotosLarge-Scale Visual Geo-Localization10.1007/978-3-319-25781-5_3(41-58)Online publication date: 6-Jul-2016
    • (2013)Discovering Latent Clusters from Geotagged Beach ImagesAdvances in Multimedia Modeling10.1007/978-3-642-35728-2_13(133-142)Online publication date: 2013

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