• DocumentCode
    2464214
  • Title

    Facial feature detection by saccadic exploration of the Gabor decomposition

  • Author

    Smeraldi, F. ; Bigün, J.

  • Author_Institution
    Microprocess. & Interface Lab., Swiss Federal Inst. of Technol., Lausanne, Switzerland
  • fYear
    1998
  • fDate
    4-7 Oct 1998
  • Firstpage
    163
  • Abstract
    The Gabor decomposition is a ubiquitous tool in computer vision. Nevertheless, it is generally considered computationally demanding for active vision applications. We suggest an attention-driven approach to feature detection inspired by the human saccadic system. A dramatic speedup is achieved by computing the Gabor decomposition only on the points of a sparse retinotopic grid. An application to eye detection is presented. Also, a real-time head detection and tracking system based on our approach is briefly discussed. The system features a novel eyeball-mounted camera designed to mimic the dynamic performance of the human eye and is, to the best of our knowledge, the first example of active vision system based on the Gabor decomposition
  • Keywords
    active vision; eye; face recognition; feature extraction; image sampling; real-time systems; search problems; tracking; visual perception; Gabor decomposition; active vision applications; active vision system; attention-driven approach; computer vision; dynamic performance; eye detection; eyeball-mounted camera; facial feature detection; human saccadic system; image sampling; real-time head detection system; real-time head tracking system; saccadic exploration; sparse retinotopic grid; Application software; Cameras; Computer vision; Face detection; Facial features; Grid computing; Humans; Machine vision; Pervasive computing; Real time systems;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Image Processing, 1998. ICIP 98. Proceedings. 1998 International Conference on
  • Conference_Location
    Chicago, IL
  • Print_ISBN
    0-8186-8821-1
  • Type

    conf

  • DOI
    10.1109/ICIP.1998.999007
  • Filename
    999007