|Department of Engineering|
|University of Cambridge > Engineering Department > Machine Intelligence Lab|
FINDING INITIAL ESTIMATES OF HUMAN FACE LOCATION
Kin Choong Yow and Roberto Cipolla
This paper describes a method to find initial estimates of face location in an image where the orientation and viewpoint of the faces are not known. Features such as eyes, nose and mouth are detected from the image using quadrature phase filters and grouped into potential face candidates. Affine invariants are used in grouping to overcome the problem of variation in viewpoint. An efficient searching algorithm is proposed to group these features based on the constraints in the geometry. Each face candidate is then evaluated using a belief network which assigns probabilities to each face candidate and rejects improbable ones. A result of 93% accuracy in detecting viewpoint variations is obtained.
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