• DocumentCode
    2935583
  • Title

    Why meaningful automatic tagging of images is very hard

  • Author

    Pavlidis, Theo

  • Author_Institution
    Stony Brook Univ., Stony Brook, NY, USA
  • fYear
    2009
  • fDate
    June 28 2009-July 3 2009
  • Firstpage
    1432
  • Lastpage
    1435
  • Abstract
    The paper points out that while automatic image tagging is often studied in connection with content-based image retrieval (CBIR), it is actually a much harder problem. Given the difficulty of the latter, the prospects for automatic image tagging do not appear promising. A brief survey of the current state of the art confirms that conclusion. Then the paper discusses an effort to tag images based on nonpixel data and proceeds with the outline of a case where the difficulty of automatic tagging is taken advantage to construct image based CAPTCHA to distinguish human users from Web-bots. That has led to certain interesting approaches to achieve reliable human tagging that is needed for the CAPTCHA application.
  • Keywords
    Internet; content-based retrieval; image retrieval; CAPTCHA application; CBIR; Web-bot; automatic image tagging; content-based image retrieval; Birds; Content based retrieval; Humans; Image retrieval; Information retrieval; Labeling; Pixel; Statistical distributions; Statistics; Tagging; CAPTCHA; CBIR; Content-Based Image Retrieval; EXIF; Image Tagging;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Multimedia and Expo, 2009. ICME 2009. IEEE International Conference on
  • Conference_Location
    New York, NY
  • ISSN
    1945-7871
  • Print_ISBN
    978-1-4244-4290-4
  • Electronic_ISBN
    1945-7871
  • Type

    conf

  • DOI
    10.1109/ICME.2009.5202771
  • Filename
    5202771