Comparative performance of different skin chrominance models and chrominance spaces for the automatic detection of human faces in color images

By Jean-Christophe Terrillon, Hideo Fukamachi, Shigeru Akamatsu, Mahdad Nouri Shirazi. Proceedings Fourth IEEE International Conference on Automatic Face and Gesture Recognition (Cat. No. PR00580), 2000

474 citations recorded by the source corpus.

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Large-scale privacy protection in Google Street View (2009, methodology): “The use of skin color in face detection has been widely explored in the literature ([3]); our approach is related to [7], and our choice of hue-saturation space is supported by the ﬁndings in [6].”
Face detection in color images (2002, methodology): “’s [15] comparison of the nine color spaces for face detection, we use the YC bCr space since it is widely used in video compression standards.”
Skin segmentation using color pixel classification: analysis and comparison (2005, background): “Terrillon et al. [6] compared Gaussian and Gaussian mixture models across nine chrominance spaces on a set of 110 images of 30 Asian and Caucasian people.”
A survey of skin-color modeling and detection methods (2007, methodology): “[102] have evaluated nine different chrominance spaces (normalized rg, CIE-xy, CIE-DSH, TSL, HSV,YES,YIQ, CIE-Lab, CIE-Luv) for skin segmentation with SGMs and GMMs on a data set of 100 images with 144 faces and 65 subjects (30 Asians, 34 Caucasians, 1 African).”
Face Detection: A Survey (2001, background): “[188] recently presented a comparative study of several widely used color spaces (or more appropriately named chrominance spaces in this context since all spaces seeks luminance-invariance) for face detection.”