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Region-based landmark discovery by crowdsourcing geo-referenced photos

Published: 24 July 2011 Publication History

Abstract

We propose a novel model for landmark discovery that locates region-based landmarks on map in contrast to the traditional point-based landmarks. The proposed method preserves more information and automatically identifies candidate regions on map by crowdsourcing geo-referenced photos. Gaussian kernel convolution is applied to remove noises and generate detected region. We adopt F1 measure to evaluate discovered landmarks and manually check the association between tags and regions. The experiment results show that more than 90% of attractions in the selected city can be correctly located by this method.

References

[1]
Crandall et al. Mapping the World's Photos. WWW 2009.
[2]
Zhang et al. Tour the world: Building a web-scale landmark recognition engine. CVPR 2009.
[3]
Singh et al. Social Pixels: Genesis and Evaluation. ACM MM 2010.

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  • (2012)Clustering-based burst-detection algorithm for web-image document stream on social media2012 IEEE International Conference on Systems, Man, and Cybernetics (SMC)10.1109/ICSMC.2012.6377809(703-708)Online publication date: Oct-2012

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  1. Region-based landmark discovery by crowdsourcing geo-referenced photos

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      cover image ACM Conferences
      SIGIR '11: Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval
      July 2011
      1374 pages
      ISBN:9781450307574
      DOI:10.1145/2009916

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      Association for Computing Machinery

      New York, NY, United States

      Publication History

      Published: 24 July 2011

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      Author Tags

      1. crowdsourcing
      2. geo-referenced photo.
      3. region-based

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      Overall Acceptance Rate 792 of 3,983 submissions, 20%

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      • (2012)Clustering-based burst-detection algorithm for web-image document stream on social media2012 IEEE International Conference on Systems, Man, and Cybernetics (SMC)10.1109/ICSMC.2012.6377809(703-708)Online publication date: Oct-2012

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