• DocumentCode
    2483615
  • Title

    Automatic face and facial features initialization for robust and accurate tracking

  • Author

    Al Haj, Murad ; Orozco, Javier ; Gonzàlez, Jordi ; Villanueva, Juan J.

  • Author_Institution
    Centre de Visio per Computador, Univ. Autonoma de Barcelona, Barcelona
  • fYear
    2008
  • fDate
    8-11 Dec. 2008
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    Face detection and tracking, through image sequences, are primary steps in many applications such as video surveillance, human computer interface, and expression analysis. Many currently existing techniques donpsilat perform well due to pose variations, appearance changes, illumination changes, complex backgrounds, and inaccurate initialization. The last short coming, which is the difficulty to initialize motion regions, is a problem facing any tracker. In this paper, we present an automatic and robust face detection and tracking system for color image sequences. Face detection is done using skin color segmentation and connected components analysis. Later, facial features are detected by active shape models and a face mesh is initialized. Finally, the tracking is done by active appearance models. Experimental detection and tracking results on a pose varying face video are given.
  • Keywords
    face recognition; feature extraction; image colour analysis; image segmentation; image sequences; mesh generation; automatic robust face detection; color image sequence; connected components analysis; expression analysis; face mesh initialization; facial feature initialization; human computer interface; robust tracking system; skin color segmentation; video surveillance; Application software; Color; Computer interfaces; Face detection; Facial features; Humans; Image analysis; Image sequences; Robustness; Video surveillance;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Pattern Recognition, 2008. ICPR 2008. 19th International Conference on
  • Conference_Location
    Tampa, FL
  • ISSN
    1051-4651
  • Print_ISBN
    978-1-4244-2174-9
  • Electronic_ISBN
    1051-4651
  • Type

    conf

  • DOI
    10.1109/ICPR.2008.4761520
  • Filename
    4761520