8.4. Face Detection and Eye Localization

Face (and eye) detection can be viewed as a two-category classification problem. Given an image patch, a face detector decides whether the patch contains a human face (class ω1) (class ω0). Misclassification happens when the face detector misses a facial image patch (false rejection) or mistakenly raises a flag on a normal, nonfacial image (false acceptance). According to Bayes's decision theory, the decision rule for the two-category classification problem can be designed by the likelihood ratio (see Eq. 7.4.2):

Equation 8.4.1

where T is the threshold and p(x|ωi) is the likelihood density of class ω

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