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      • Department of Computer Engineering
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      Automatic tag expansion using visual similarity for photo sharing websites

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      Author(s)
      Sevil, S. G.
      Kucuktunc, O.
      Duygulu, P.
      Can, F.
      Date
      2010
      Source Title
      Multimedia Tools and Applications
      Print ISSN
      1380-7501
      Publisher
      Springer New York LLC
      Volume
      49
      Issue
      1
      Pages
      81 - 99
      Language
      English
      Type
      Article
      Item Usage Stats
      228
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      237
      downloads
      Abstract
      In this paper we present an automatic photo tag expansion method designed for photo sharing websites. The purpose of the method is to suggest tags that are relevant to the visual content of a given photo at upload time. Both textual and visual cues are used in the process of tag expansion. When a photo is to be uploaded, the system asks for a couple of initial tags from the user. The initial tags are used to retrieve relevant photos together with their tags. These photos are assumed to be potentially content related to the uploaded target photo. The tag sets of the relevant photos are used to form the candidate tag list, and visual similarities between the target photo and relevant photos are used to give weights to these candidate tags. Tags with the highest weights are suggested to the user. The method is applied on Flickr (http://www.flickr. com ). Results show that including visual information in the process of photo tagging increases accuracy with respect to text-based methods. © 2009 Springer Science+Business Media, LLC.
      Keywords
      Flickr
      Folksonomy
      Photo-annotation
      Tagging
      Visual similarity
      Expansion methods
      Folksonomies
      Photo sharing
      Text-based methods
      Visual content
      Visual cues
      Visual information
      Digital storage
      Semantic web
      Visual communication
      Permalink
      http://hdl.handle.net/11693/22264
      Published Version (Please cite this version)
      http://dx.doi.org/10.1007/s11042-009-0394-5
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      • Department of Computer Engineering 1510
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