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