• DocumentCode
    597893
  • Title

    Beard and mustache segmentation using sparse classifiers on self-quotient images

  • Author

    Le, T. Hoang Ngan ; Khoa Luu ; Seshadri, K. ; Savvides, Marios

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Carnegie Mellon Univ., Pittsburgh, PA, USA
  • fYear
    2012
  • fDate
    Sept. 30 2012-Oct. 3 2012
  • Firstpage
    165
  • Lastpage
    168
  • Abstract
    In this paper, we propose a novel system for beard and mustache detection and segmentation in challenging facial images. Our system first eliminates illumination artifacts using the self-quotient algorithm. A sparse classifier is then used on these self-quotient images to classify a region as either containing skin or facial hair. We conduct experiments on the MBGC and color FERET databases to demonstrate the effectiveness of our proposed system.
  • Keywords
    image classification; image segmentation; object detection; visual databases; MBGC database; beard detection; beard segmentation; color FERET database; facial hair; facial image; illumination artifact; mustache detection; mustache segmentation; self-quotient algorithm; self-quotient image; skin; sparse classifier; Databases; Face; Hair; Image color analysis; Image segmentation; Lighting; Skin; Beard/mustache detection; segmentation; self-quotient image; sparse classifier;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Image Processing (ICIP), 2012 19th IEEE International Conference on
  • Conference_Location
    Orlando, FL
  • ISSN
    1522-4880
  • Print_ISBN
    978-1-4673-2534-9
  • Electronic_ISBN
    1522-4880
  • Type

    conf

  • DOI
    10.1109/ICIP.2012.6466821
  • Filename
    6466821