Detecting Faces in Images: A Survey
IEEE Transactions on Pattern Analysis and Machine Intelligence
International Journal of Computer Vision - Special issue on statistical and computational theories of vision: Part II
A Neural Network Architecture for Visual Selection
Neural Computation
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We describe a method of locating hypotheses for the positions of faces in an image. We use statistical feature detectors to locate candidates for features, then use a statistical model of the shape and orientation of the features to test combinations of such features to find the most plausible. The best sets can be used as the initial position of an Active Shape Model, which can then accurately locate the full face.