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<p><b>Abstract</b>—We present an example-based learning approach for locating vertical frontal views of human faces in complex scenes. The technique models the distribution of human face patterns by means of a few view-based "face" and "nonface" model clusters. At each image location, a difference feature vector is computed between the local image pattern and the distribution-based model. A trained classifier determines, based on the difference feature vector measurements, whether or not a human face exists at the current image location. We show empirically that the distance metric we adopt for computing difference feature vectors, and the "nonface" clusters we include in our distribution-based model, are both critical for the success of our system.</p>
Face detection, object detection, example-based learning, example selection, pattern recognition, view-based recognition, density estimation, Gaussian mixture model.

T. Poggio and K. Sung, "Example-Based Learning for View-Based Human Face Detection," in IEEE Transactions on Pattern Analysis & Machine Intelligence, vol. 20, no. , pp. 39-51, 1998.
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