Face Detection and Modeling for Recognition - Biometrics Research ...

center, and lengths of major and minor axes. Since we know the locations of eyes and
mouth, the orientation of the ellipse can be estimated from the direction of a vector
that starts from the midpoint between the eyes towards the mouth. The location of
the ellipse center is estimated from the face boundary map. Hence, we need only a
two-dimensional accumulator for estimating the ellipse for bounding the face. The
accumulator is updated by perturbing the estimated center by a few pixels for a more
accurate localization of the ellipse.
3.3.5 Weight Selection for a Face Candidate
For each face in the image, our algorithm can detect several eye-mouth-triangle candidates
that are constructed from eye and mouth candidates. Each candidate is assigned
a weight which is computed from the eye and mouth maps, the maximum accumulator
count in the Hough transform for ellipse fitting, and face orientation that favors
vertical faces and symmetric facial geometry, as described in Eqs. (3.15)-(3.19). The
eye-mouth triangle with the highest weight (face score) that is above a threshold is
retained. In Eq. (3.15), the triangle weight, tw(i, j, k), for the i-th and the j-th eye
candidates and the k-th mouth candidate is the product of the eye-mouth weight,
emw(i, j, k), the face-orientation weight, ow(i, j, k), and boundary quality, q(i, j, k).
The eye-mouth weight is the average of the eye-pair weight, ew(i, j), and the mouth
weight, mw(k), as described in Eq. (3.16).
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