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GPS estimation from users' photos

  • Jing Li
  • , Xueming Qian
  • , Yuan Yan Tang
  • , Linjun Yang
  • , Chaoteng Liu
  • Xi'an Jiaotong University
  • University of Macau
  • Microsoft USA

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

20 Scopus citations

Abstract

Nowadays social media are very popular for people to share their photos with their friends. Many of the photos are geo-tagged (with GPS information) whether automatically or manually. Social media management websites such as Flickr allow users manually labeling their uploaded photos with GPS with the interface of dragging them into the map. However, manually dragging the photos to the map will bring more error and very boring for users to labeling their photos. Thus in this paper, a GPS location estimation approach is proposed. For an uploaded image, its GPS information is estimated by both hierarchical global feature classification and local feature refinement to guarantee the accuracy and computational cost. To guarantee the estimation performances, k-nearest neighbors are selected in global feature classification stage. Experiments show the effectiveness of our proposed approach.

Original languageEnglish
Title of host publicationAdvances in Multimedia Modeling - 19th International Conference, MMM 2013, Proceedings
PublisherSpringer Verlag
Pages118-129
Number of pages12
EditionPART 1
ISBN (Print)9783642357244
DOIs
StatePublished - 2013
Event19th International Conference on Advances in Multimedia Modeling, MMM 2013 - Huangshan, China
Duration: 7 Jan 20139 Jan 2013

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 1
Volume7732 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference19th International Conference on Advances in Multimedia Modeling, MMM 2013
Country/TerritoryChina
CityHuangshan
Period7/01/139/01/13

Keywords

  • BoW
  • GPS estimation
  • Geo-tag
  • Hierarchical structure
  • K-NN

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