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Matthias Wimmer and Bernd Radig. Adaptive Skin Color Classificator. ICGST International Journal on Graphics, Vision and Image Processing, Special Issue on Biometrics, 2006.

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Abstract

Skin color is an important feature of faces. Various applications benefit from robust skin color detection. Skin color may look quite different, depending on camera settings, illumination, shadows, people's tans, ethnic groups. That variation is a challenging aspect of skin color classification. In this paper, we present an approach that uses a high level vision module to detect an image specific skin color model. This model is representative for the context conditions within the image and is used to adapt dynamic skin color classifiers to it. This approach distinguishes skin color from very similar color like lip color or eyebrow color. Its high speed and accuracy makes it appropriate for real time applications such as face model fitting, gaze estimation, and recognition of facial expressions.

BibTeX Entry

@article{wimmer06adaptive,
  AUTHOR   			= {Matthias Wimmer and Bernd Radig},
  TITLE    			= {Adaptive Skin Color Classificator},
  JOURNAL  			= {ICGST International Journal on Graphics, Vision and Image Processing},
  YEAR     			= {2006},
  VOLUME   			= {Special Issue on Biometrics},
  abstract			= 
  						{Skin color is an important feature of faces. Various applications benefit from robust skin color detection. Skin color may look quite different, depending on camera settings, illumination, shadows, people's tans, ethnic groups. That variation is a challenging aspect of skin color classification. In this paper, we present an approach that uses a high level vision module to detect an image specific skin color model. This model is representative for the context conditions within the image and is used to adapt dynamic skin color classifiers to it. This approach distinguishes skin color from very similar color like lip color or eyebrow color. Its high speed and accuracy makes it appropriate for real time applications such as face model fitting, gaze estimation, and recognition of facial expressions.},
  bib2html_pubtype	= {Journal},
  bib2html_rescat   = {Image Understanding},
  bib2html_groups   = {IU},
}

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