• DocumentCode
    74066
  • Title

    Tag Features for Geo-Aware Image Classification

  • Author

    Shuai Liao ; Xirong Li ; Heng Tao Shen ; Yang Yang ; Xiaoyong Du

  • Author_Institution
    Key Lab. of Data Eng. & Knowledge Eng., Renmin Univ. of China, Beijing, China
  • Volume
    17
  • Issue
    7
  • fYear
    2015
  • fDate
    Jul-15
  • Firstpage
    1058
  • Lastpage
    1067
  • Abstract
    The use of geo tags in recording the location at which a picture was taken is becoming part of image metadata . Therefore , studying approaches to image classification that can favorably exploit both geo tags and the underlying geo context has become an emerging topic. This paper contributes to geo-aware image classification by studying how to encode geo information into image representation. Given a geo-tagged image, we propose to extract geo-aware tag features by tag propagation from the geo and visual neighbors of the given image. Depending on what neighbors are used and how they are weighted, we present and compare eight variants of geo-aware tag features. Using millions of Flickr images as source data for tag feature extraction, experiments on a popular benchmark set justify the effectiveness and robustness of the proposed tag features for geo-aware image classification.
  • Keywords
    feature extraction; geographic information systems; image classification; image representation; meta data; Flickr images; geo information; geo-aware image classification; geo-tagged image; image metadata; image representation; tag feature extraction; tag features; tag propagation; visual neighbors; Cities and towns; Context; Feature extraction; Media; Robustness; Semantics; Visualization; Geo tags; geo-aware image classification; tag features;
  • fLanguage
    English
  • Journal_Title
    Multimedia, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1520-9210
  • Type

    jour

  • DOI
    10.1109/TMM.2015.2436057
  • Filename
    7111322