• DocumentCode
    3136634
  • Title

    Unsupervised clustering for google searches of celebrity images

  • Author

    Holub, Alex ; Moreels, Pierre ; Perona, Pietro

  • Author_Institution
    California Inst. of Technol., Pasadena, CA
  • fYear
    2008
  • fDate
    17-19 Sept. 2008
  • Firstpage
    1
  • Lastpage
    8
  • Abstract
    How do we identify images of the same person in photo albums? How can we find images of a particular celebrity using Web image search engines? These types of tasks require solving numerous challenging issues in computer vision including: detecting whether an image contains a face, maintaining robustness to lighting, pose, occlusion, scale, and image quality, and using appropriate distance metrics to identify and compare different faces. In this paper we present a complete system which yields good performance on challenging tasks involving face recognition including image retrieval, unsupervised clustering of faces, and increasing precision of dasiaGoogle Imagepsila searches. All tasks use highly variable real data obtained from raw image searches on the web.
  • Keywords
    Internet; computer vision; face recognition; hidden feature removal; image retrieval; object detection; pattern clustering; pose estimation; search engines; unsupervised learning; Google search engine; Web image retrieval; celebrity image detection; computer vision; distance metrics; face recognition; image quality; occlusion method; pose estimation; unsupervised clustering; Computer vision; Eyebrows; Eyes; Face detection; Face recognition; Image quality; Mouth; Nose; Robustness; Search engines;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Automatic Face & Gesture Recognition, 2008. FG '08. 8th IEEE International Conference on
  • Conference_Location
    Amsterdam
  • Print_ISBN
    978-1-4244-2153-4
  • Electronic_ISBN
    978-1-4244-2154-1
  • Type

    conf

  • DOI
    10.1109/AFGR.2008.4813463
  • Filename
    4813463