Bayes rule
In terms of
our problem:
what we
measure
(likelihood)
domain
knowledge
(prior)
what we want
(posterior)
normalization term
The prior:
P(skin)
•Could use domain knowledge
–P(skin) may be larger if we know the image contains a
person
–for a portrait, P(skin) may be higher for pixels in the
center
•Could learn the prior from the training set. How?
–P(skin) may be proportion of skin pixels in training set
