Learning conditional PDF’s
	We can calculate P(R | skin) from a set of training images • It is simply a histogram over the pixels in the training images – each bin Ri contains the proportion of skin pixels with color Ri
	This doesn’t work as well in higher-dimensional spaces.  Why not?
						Approach:  fit parametric PDF functions • common choice is rotated Gaussian – center – covariance » orientation, size defined by eigenvecs, eigenvals