A Person and Context Specific Approach for Skin Color Classification (bibtex)
by M Wimmer, B Radig and M Beetz
Abstract:
Skin color is an important feature of faces. Various applications benefit from robust skin color detection. Depending on camera settings, illumination, shadows, people?s tans, and ethnic groups skin color looks differently, which is a challenging aspect for detecting it automatically. 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 then used to adapt parametric skin color classifiers to the processed image. This approach is capable to distinguish skin color from extremely similar colors, such as lip color or eyebrow color. Its high speed and high accuracy make it appropriate for real time applications such as face tracking and recognition of facial expressions.
Reference:
A Person and Context Specific Approach for Skin Color Classification (M Wimmer, B Radig and M Beetz), In Procedings of the 18th International Conference of Pattern Recognition (ICPR 2006), IEEE Computer Society, volume 2, 2006. 
Bibtex Entry:
@inproceedings{wimmer_person_2006,
 author = {M Wimmer and B Radig and M Beetz},
 title = {A Person and Context Specific Approach for Skin Color Classification},
 booktitle = {Procedings of the 18th International Conference of Pattern Recognition
	({ICPR} 2006)},
 year = {2006},
 volume = {2},
 pages = {39--42},
 address = {Los Alamitos, {CA}, {USA}},
 month = {aug},
 publisher = {{IEEE} Computer Society},
 abstract = {Skin color is an important feature of faces. Various applications
	benefit from robust skin color detection. Depending on camera settings,
	illumination, shadows, people?s tans, and ethnic groups skin color
	looks differently, which is a challenging aspect for detecting it
	automatically. 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 then used to adapt parametric skin color classifiers
	to the processed image. This approach is capable to distinguish skin
	color from extremely similar colors, such as lip color or eyebrow
	color. Its high speed and high accuracy make it appropriate for real
	time applications such as face tracking and recognition of facial
	expressions.},
}
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A Person and Context Specific Approach for Skin Color Classification (bibtex)
A Person and Context Specific Approach for Skin Color Classification (bibtex)
by M Wimmer, B Radig and M Beetz
Abstract:
Skin color is an important feature of faces. Various applications benefit from robust skin color detection. Depending on camera settings, illumination, shadows, people?s tans, and ethnic groups skin color looks differently, which is a challenging aspect for detecting it automatically. 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 then used to adapt parametric skin color classifiers to the processed image. This approach is capable to distinguish skin color from extremely similar colors, such as lip color or eyebrow color. Its high speed and high accuracy make it appropriate for real time applications such as face tracking and recognition of facial expressions.
Reference:
A Person and Context Specific Approach for Skin Color Classification (M Wimmer, B Radig and M Beetz), In Procedings of the 18th International Conference of Pattern Recognition (ICPR 2006), IEEE Computer Society, volume 2, 2006. 
Bibtex Entry:
@inproceedings{wimmer_person_2006,
 author = {M Wimmer and B Radig and M Beetz},
 title = {A Person and Context Specific Approach for Skin Color Classification},
 booktitle = {Procedings of the 18th International Conference of Pattern Recognition
	({ICPR} 2006)},
 year = {2006},
 volume = {2},
 pages = {39--42},
 address = {Los Alamitos, {CA}, {USA}},
 month = {aug},
 publisher = {{IEEE} Computer Society},
 abstract = {Skin color is an important feature of faces. Various applications
	benefit from robust skin color detection. Depending on camera settings,
	illumination, shadows, people?s tans, and ethnic groups skin color
	looks differently, which is a challenging aspect for detecting it
	automatically. 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 then used to adapt parametric skin color classifiers
	to the processed image. This approach is capable to distinguish skin
	color from extremely similar colors, such as lip color or eyebrow
	color. Its high speed and high accuracy make it appropriate for real
	time applications such as face tracking and recognition of facial
	expressions.},
}
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