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Generating representative images for landmark by discovering high frequency shooting locations from community-contributed photos

  • Xi'an Jiaotong University

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

17 Scopus citations

Abstract

Representative images generation offers a comprehensive knowledge for landmark and is a hot research area recent years. This paper presents a representative images generation system by discovering high frequency shooting locations from geo-tagged community-contributed photos. We discover that the views (e.g. far and near, front, back and side) of the photos taken in the same location are usually similar and but different in different shooting locations. Our system is realized by three steps: 1) Landmark dataset is filtered from social media by the combination of tags and geo-tags. 2) High frequency shooting locations are mined by geo-tag cluster. 3) Visual feature is then used for removing irrelevant images and ranking by intra and inter SIFT matching. This work is the first attempt to generate representative images by high frequency shooting locations mining. Evaluating on ten landmarks shows its effectiveness.

Original languageEnglish
Title of host publicationElectronic Proceedings of the 2013 IEEE International Conference on Multimedia and Expo Workshops, ICMEW 2013
DOIs
StatePublished - 2013
Event2013 IEEE International Conference on Multimedia and Expo Workshops, ICMEW 2013 - San Jose, CA, United States
Duration: 15 Jul 201319 Jul 2013

Publication series

NameElectronic Proceedings of the 2013 IEEE International Conference on Multimedia and Expo Workshops, ICMEW 2013

Conference

Conference2013 IEEE International Conference on Multimedia and Expo Workshops, ICMEW 2013
Country/TerritoryUnited States
CitySan Jose, CA
Period15/07/1319/07/13

Keywords

  • Geo-tagged photos
  • Representative Image Selection
  • social media

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