The colors of the human skin represent a special
category of colors, because they are distinctive from the colors of
other natural objects. This category is found as a cluster in color
spaces, and the skin color variations between people are mostly due
to differences in the intensity. Besides, the face detection based on
skin color detection is a faster method as compared to other
techniques. In this work, we present a system to track faces by
carrying out skin color detection in four different color spaces: HSI,
YCbCr, YES and RGB. Once some skin color regions have been
detected for each color space, we label each and get some
characteristics such as size and position. We are supposing that a face
is located in one the detected regions. Next, we compare and employ
a polling strategy between labeled regions to determine the final
region where the face effectively has been detected and located.
 M. Yang, D. J. Kriegman and N. Ahuja, "Detecting Faces in Images: A
Survey", IEEE Trans. on PAMI, vol. 24, no. 1, pp. 34-58, Jan 2002.
 R. Hsu and M. Abdel-Mottaleb, "Face Detection in Color Images," IEEE
Trans. on PAMI, vol. 24, no. 5, pp. 696-706, May 2002.
 S. K. Singh, D. S. Chauhan, M. Vatsa and R. Singh, "A Robust Skin
Color Based Face Detection Algorithm", Tamkang Journal of Science
and Engineering, vol. 6, no. 4, pp. 227-234, 2003.
 J. Liu and Y. H. Yang, "Multiresolution color image segmentation",
IEEE Trans. on PAMI, vol. 16, pp. 689-700, July 1994.
 D. H. Ballard and C. Brown. Computer Vision. Prentice Hall, Inc.,
Englewood Cliffs, New Jersey, 1982.