Extraction of face region by using characteristics of color space and detection of face direction through an eigenspace

Five color spaces, RGB, XYZ, YIQ, HSV and LUV color spaces, were examined to know which was the most suitable to extract face regions. From the observations of flesh-colored pixel distributions in those color spaces, an ellipse from the UV plane in the LUV color space successfully extracted a face region. A proposed method using LUV color space and ellipse extraction was an extension of the method proposed by (Hongo et al., 1998) that used a circle instead of an ellipse, and it improved extracted results by 6% in our agreement index defined in this paper. Extracted rotated face images by 20 degrees interval were used to make an automatic face direction detection system. The face direction was estimated through two processes. The first process was a projection into an eigenspace, and the second process was an estimation of direction by a neural network. At first, a seven-dimensional eigenspace was obtained from the principal component analysis of ten face images. Then, a neural network learned to detect the face direction by using the projected coordinates of these images in the eigenspace