• DocumentCode
    2917283
  • Title

    Image annotation through gaming (TAG4FUN)

  • Author

    Seneviratne, L. ; Izquierdo, E.

  • Author_Institution
    Multimedia & Vision Res. Group, Queen Mary, Univ. of London, London, UK
  • fYear
    2009
  • fDate
    5-7 July 2009
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    This paper introduces a new technique for image annotation in which social aspects of human-based computation are exploited. The proposed approach aims at exploiting what millions of single, online and cooperative gamers are keen to do, (in some cases gaming enthusiasts) to tackle the challenging image annotation task. The proposed approach deviates from the conventional "content-based image retrieval (CBIR)" paradigm, favored by the research community to tackle problems related to semantic annotation and tagging of multimedia content. The proposed approach focuses on social aspects of gaming and the use of humans in a widely distributed fashion through a process of human-based computation. It aims at motivating people towards image tagging while entertaining themselves. Regarding key aspect of label accuracy, a combination of computer vision techniques, machine learning and game strategies have been used.
  • Keywords
    computer games; computer vision; content-based retrieval; human factors; image retrieval; interactive systems; learning (artificial intelligence); TAG4FUN game; computer vision technique; content-based image retrieval; cooperative gamer; human-based computation; image annotation; image tagging; interactive game; machine learning; multimedia content; semantic annotation; Computer vision; Content based retrieval; Games; Humans; Image retrieval; Labeling; Machine learning; Object recognition; Psychology; Tagging; Image Annotation; Interactive gaming; Lowlevel feature extraction and object recognition;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Digital Signal Processing, 2009 16th International Conference on
  • Conference_Location
    Santorini-Hellas
  • Print_ISBN
    978-1-4244-3297-4
  • Electronic_ISBN
    978-1-4244-3298-1
  • Type

    conf

  • DOI
    10.1109/ICDSP.2009.5201118
  • Filename
    5201118