• DocumentCode
    248828
  • Title

    Benchmarking result diversification in social image retrieval

  • Author

    Ionescu, Bogdan ; Popescu, Adrian ; Muller, Holger ; Menendez, Maria ; Radu, Anca-Livia

  • Author_Institution
    Univ. Politeh. of Bucharest, Bucharest, Romania
  • fYear
    2014
  • fDate
    27-30 Oct. 2014
  • Firstpage
    3072
  • Lastpage
    3076
  • Abstract
    This article addresses the issue of retrieval result diversification in the context of social image retrieval and discusses the results achieved during the MediaEval 2013 benchmarking. 38 runs and their results are described and analyzed in this text. A comparison of the use of expert vs. crowdsourcing annotations shows that crowdsourcing results are slightly different and have higher inter observer differences but results are comparable at lower cost. Multimodal approaches have best results in terms of cluster recall. Manual approaches can lead to high precision but often lower diversity. With this detailed results analysis we give future insights on this matter.
  • Keywords
    image retrieval; social networking (online); MediaEval 2013 benchmarking; crowdsourcing annotations; expert annotations; retrieval result diversification; social image retrieval; Benchmark testing; Cultural differences; Global Positioning System; Image retrieval; Media; Optimization; Visualization; crowdsourcing; image content description; re-ranking; result diversification; social photo retrieval;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Image Processing (ICIP), 2014 IEEE International Conference on
  • Conference_Location
    Paris
  • Type

    conf

  • DOI
    10.1109/ICIP.2014.7025621
  • Filename
    7025621